Prof. Vladimir V. Lukin Profile

Prof. Vladimir V. Lukin

Vice Chairman at Kharkiv Aviation Institute

SPIE Involvement:

Editorial Board Member: Journal of Electronic Imaging | Author

Publications (92)

Proceedings Article | 12 September 2021 Presentation + Paper

Discrete atomic compression of satellite images: a comprehensive efficiency research

Viktor Makarichev, Vladimir Lukin, Iryna Brysina, Benoit Vozel, Kacem Chehdi

Proceedings Volume 11862, 118620Q (2021) https://doi.org/10.1117/12.2599895

KEYWORDS: Image compression, Wavelets, Data processing, Chromium, Computer programming, Remote sensing, Binary data, Satellites, Image processing, Satellite imaging

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Proceedings Article | 12 September 2021 Presentation + Paper

Lossy compression of three-channel remote sensing images with controllable quality

Irina Vasilyeva, Fangfang Li, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 11862, 118620R (2021) https://doi.org/10.1117/12.2599902

KEYWORDS: Image compression, Image classification, 3D image processing, Chromium, Vegetation, Remote sensing, Image quality, Visualization, Visual compression, Transform theory

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Proceedings Article | 20 September 2020 Presentation + Paper

Atomic wavelets in lossy and near-lossless image compression

Victor Makarichev, Vladimir Lukin, Iryna Brysina, Benoit Vozel, Kacem Chehdi

Proceedings Volume 11533, 1153313 (2020) https://doi.org/10.1117/12.2573970

KEYWORDS: Image compression, Wavelets, Computing systems, Image quality, Digital imaging, Quality measurement, Visual compression, Visualization, Satellite imaging, Earth observing sensors

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Proceedings Article | 20 September 2020 Presentation + Paper

Comparison of learning-based and maximum-likelihood estimators of image noise variance for real-life and synthetic anisotropic textures

Mykhail Uss, Benoit Vozel, Vladimir Lukin, Kacem Chehdi

Proceedings Volume 11533, 1153303 (2020) https://doi.org/10.1117/12.2573934

KEYWORDS: Image analysis, Model-based design, Motion models, Signal processing, Interference (communication), Sensors, Image processing, Error analysis, Remote sensing, Intelligence systems

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Proceedings Article | 7 October 2019 Paper

Lossy DCT-based compression of remote sensing images with providing a desired visual quality

Sergey Krivenko, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 11155, 1115512 (2019) https://doi.org/10.1117/12.2532726

KEYWORDS: Image compression, Visualization, Remote sensing, Chromium, Visual compression, Image quality, Quantization, Image classification, Sensors, Data compression

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Proceedings Article | 7 October 2019 Paper

Blind noise parameters estimation for multichannel images using deep convolutional neural networks

M. Uss, B. Vozel, V. Lukin, K. Chehdi

Proceedings Volume 11155, 1115514 (2019) https://doi.org/10.1117/12.2533300

KEYWORDS: Signal to noise ratio, Interference (communication), RGB color model, Databases, Image analysis, Cameras, Remote sensing, Sensors, Error analysis, Convolutional neural networks

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Proceedings Article | 9 October 2018 Paper

Preliminary filtering and lossy compression of noisy remote sensing images

Alexander Zemliachenko, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 10789, 107890V (2018) https://doi.org/10.1117/12.2325102

KEYWORDS: Image compression, Chromium, Remote sensing, Visualization, Image quality, Image filtering, Transform theory, Optical inspection, Denoising, Image processing

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Proceedings Article | 9 October 2018 Paper

Towards a blind restoration method of hyperspectral images

Mo Zhang, Benoit Vozel, Kacem Chehdi, Mykhail Uss, Sergey Abramov, Vladimir Lukin

Proceedings Volume 10789, 107890A (2018) https://doi.org/10.1117/12.2325456

KEYWORDS: Error analysis, Point spread functions, Hyperspectral imaging, Image processing, Image analysis, Image resolution, Spatial resolution, Image classification, Denoising, Data modeling

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Proceedings Article | 9 October 2018 Paper

Using interchannel correlation in blind evaluation of noise characteristics in multichannel remote sensing images

Victoriya Abramova, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 10789, 1078909 (2018) https://doi.org/10.1117/12.2325100

KEYWORDS: Remote sensing, Interference (communication), Image processing, Image analysis, Databases, Hyperspectral imaging, Visualization, Statistical analysis, Sensors, Lab on a chip

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Proceedings Article | 10 October 2017 Paper

Output MSE and PSNR prediction in DCT-based lossy compression of remote sensing images

Ruslan Kozhemiakin, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 10427, 1042721 (2017) https://doi.org/10.1117/12.2278002

KEYWORDS: Image compression, Remote sensing, Quantization, Image quality, Error analysis, Image analysis, Data storage, Chromium, Data acquisition, Control systems

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Proceedings Article | 4 October 2017 Paper

Blind estimation of blur in hyperspectral images

Mo Zhang, Benoit Vozel, Kacem Chehdi, Mykhail Uss, Sergey Abramov, Vladimir Lukin

Proceedings Volume 10427, 104270L (2017) https://doi.org/10.1117/12.2278004

KEYWORDS: Point spread functions, Hyperspectral imaging, Error analysis, Image analysis, Remote sensing, Sensors, Data modeling, Sensing systems, Image restoration, Signal to noise ratio

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Hyperspectral images acquired by remote sensing systems are generally degraded by noise and can be sometimes more severely degraded by blur. When no knowledge is available about the degradations present on the original image, blind restoration methods can only be considered. By blind, we mean absolutely no knowledge neither of the blur point spread function (PSF) nor the original latent channel and the noise level. In this study, we address the blind restoration of the degraded channels component-wise, according to a sequential scheme. For each degraded channel, the sequential scheme estimates the blur point spread function (PSF) in a first stage and deconvolves the degraded channel in a second and final stage by means of using the PSF previously estimated. We propose a new component-wise blind method for estimating effectively and accurately the blur point spread function. This method follows recent approaches suggesting the detection, selection and use of sufficiently salient edges in the current processed channel for supporting the regularized blur PSF estimation. Several modifications are beneficially introduced in our work. A new selection of salient edges through thresholding adequately the cumulative distribution of their corresponding gradient magnitudes is introduced. Besides, quasi-automatic and spatially adaptive tuning of the involved regularization parameters is considered. To prove applicability and higher efficiency of the proposed method, we compare it against the method it originates from and four representative edge-sparsifying regularized methods of the literature already assessed in a previous work. Our attention is mainly paid to the objective analysis (via ݈l₁-norm) of the blur PSF error estimation accuracy. The tests are performed on a synthetic hyperspectral image. This synthetic hyperspectral image has been built from various samples from classified areas of a real-life hyperspectral image, in order to benefit from realistic spatial distribution of reference spectral signatures to recover after synthetic degradation. The synthetic hyperspectral image has been successively degraded with eight real blurs taken from the literature, each of a different support size. Conclusions, practical recommendations and perspectives are drawn from the results experimentally obtained.

Proceedings Article | 4 October 2017 Paper

Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

M. Uss, B. Vozel, V. Lukin, K. Chehdi

Proceedings Volume 10427, 104270Y (2017) https://doi.org/10.1117/12.2278007

KEYWORDS: Signal to noise ratio, Image compression, Sensors, Remote sensing, Hyperspectral imaging, Interference (communication), Signal processing, Image analysis, Image filtering, Data modeling

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Proceedings Article | 18 October 2016 Paper

Scatter-plot-based method for noise characteristics evaluation in remote sensing images using adaptive image clustering procedure

Victoriya Abramova, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 10004, 1000408 (2016) https://doi.org/10.1117/12.2240876

KEYWORDS: Interference (communication), Image segmentation, Image processing, Image analysis, Remote sensing, Databases, Lab on a chip, Data processing, Bismuth, Solids

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Proceedings Article | 18 October 2016 Paper

Efficiency analysis for 3D filtering of multichannel images

Ruslan Kozhemiakin, Oleksii Rubel, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 10004, 1000406 (2016) https://doi.org/10.1117/12.2240865

KEYWORDS: Signal processing, Image filtering, Denoising, Filtering (signal processing), Remote sensing, 3D image processing, Signal to noise ratio, Statistical analysis, Image processing, Interference (communication)

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Proceedings Article | 18 October 2016 Paper

Statistical power of intensity- and feature-based similarity measures for registration of multimodal remote sensing images

M. Uss, B. Vozel, V. Lukin, K. Chehdi

Proceedings Volume 10004, 1000403 (2016) https://doi.org/10.1117/12.2240895

KEYWORDS: Matrices, Visual process modeling, Image registration, Remote sensing, Radar, Interference (communication), Image processing, Samarium, Lawrencium, Motion models

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Proceedings Article | 18 October 2016 Paper

Accuracy assessment of blind and semi-blind restoration methods for hyperspectral images

Mo Zhang, Benoit Vozel, Kacem Chehdi, Mykhail Uss, Sergey Abramov, Vladimir Lukin

Proceedings Volume 10004, 100040P (2016) https://doi.org/10.1117/12.2240950

KEYWORDS: Hyperspectral imaging, Image filtering, Interference (communication), Remote sensing, Point spread functions, Error analysis, Signal to noise ratio, Image analysis, Image restoration, Information operations

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Proceedings Article | 15 October 2015 Paper

Performance prediction for 3D filtering of multichannel images

Oleksii Rubel, Ruslan Kozhemiakin, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 9643, 96430D (2015) https://doi.org/10.1117/12.2193976

KEYWORDS: Electronic filtering, Denoising, Image filtering, Statistical analysis, Signal to noise ratio, Filtering (signal processing), 3D image processing, Image processing, Remote sensing, Image quality

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Proceedings Article | 15 October 2015 Paper

Potential accuracy of translation estimation between radar and optical images

M. Uss, B. Vozel, V. Lukin, K. Chehdi

Proceedings Volume 9643, 96430W (2015) https://doi.org/10.1117/12.2194071

KEYWORDS: Earth observing sensors, Image filtering, Californium, Radar, Image registration, Speckle, Signal to noise ratio, Interference (communication), Landsat, Image analysis

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SPIE Journal Paper | 11 August 2015 Open Access

Lossy compression of noisy remote sensing images with prediction of optimal operation point existence and parameters

Alexander Zemliachenko, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

JARS, Vol. 9, Issue 01, 095066, (August 2015) https://doi.org/10.1117/12.10.1117/1.JRS.9.095066

KEYWORDS: Image compression, Remote sensing, Chromium, Visualization, Image quality, Quantization, Interference (communication), Visual compression, Data compression, Hyperspectral imaging

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Proceedings Article | 17 March 2015 Paper

Combining full-reference image visual quality metrics by neural network

Vladimir Lukin, Nikolay Ponomarenko, Oleg Ieremeiev, Karen Egiazarian, Jaakko Astola

Proceedings Volume 9394, 93940K (2015) https://doi.org/10.1117/12.2085465

KEYWORDS: Image quality, Molybdenum, Visualization, Neural networks, Databases, Image visualization, Neurons, Image denoising, Statistical analysis, Fabry–Perot interferometers

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Proceedings Article | 16 March 2015 Paper

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

Aleksey Rubel, Vladimir Lukin, Karen Egiazarian

Proceedings Volume 9399, 93990P (2015) https://doi.org/10.1117/12.2082533

KEYWORDS: Denoising, Image filtering, Image processing, Signal to noise ratio, Visualization, Image quality, Interference (communication), Databases, Optical filters, Statistical analysis

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Proceedings Article | 15 October 2014 Paper

Prediction of optimal operation point existence and parameters in lossy compression of noisy images

Alexander Zemliachenko, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 9244, 92440H (2014) https://doi.org/10.1117/12.2065947

KEYWORDS: Image compression, Visualization, Remote sensing, Chromium, Visual compression, Statistical analysis, Hyperspectral imaging, Denoising, Data compression, Control systems

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SPIE Journal Paper | 11 August 2014 Open Access

Lossy compression of hyperspectral images based on noise parameters estimation and variance stabilizing transform

Alexander Zemliachenko, Ruslan Kozhemiakin, Mikhail Uss, Sergey Abramov, Nikolay Ponomarenko, Vladimir Lukin, Benoît Vozel, Kacem Chehdi

JARS, Vol. 8, Issue 01, 083571, (August 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083571

KEYWORDS: Image compression, Chromium, Hyperspectral imaging, 3D image processing, Data compression, Sensors, Signal to noise ratio, Interference (communication), Image processing, Data acquisition

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A problem of lossy compression of hyperspectral images is considered. A specific aspect is that we assume a signal-dependent model of noise for data acquired by new generation sensors. Moreover, a signal-dependent component of the noise is assumed dominant compared to a signal-independent noise component. Sub-band (component-wise) lossy compression is studied first, and it is demonstrated that optimal operation point (OOP) can exist. For such OOP, the mean square error between compressed and noise-free images attains global or, at least, local minimum, i.e., a good effect of noise removal (filtering) is reached. In practice, we show how compression in the neighborhood of OOP can be carried out, when a noise-free image is not available. Two approaches for reaching this goal are studied. First, lossy compression directly applied to the original data is considered. According to another approach, lossy compression is applied to images after direct variance stabilizing transform (VST) with properly adjusted parameters. Inverse VST has to be performed only after data decompression. It is shown that the second approach has certain advantages. One of them is that the quantization step for a coder can be set the same for all sub-band images. This offers favorable prerequisites for applying three-dimensional (3-D) methods of lossy compression for sub-band images combined into groups after VST. Two approaches to 3-D compression, based on the discrete cosine transform, are proposed and studied. A first approach presumes obtaining the reference and “difference” images for each group. A second performs compression directly for sub-images in a group. We show that it is a good choice to have 16 sub-images in each group. The abovementioned approaches are tested for Hyperion hyperspectral data. It is demonstrated that the compression ratio of about 15–20 can be provided for hyperspectral image compression in the neighborhood of OOP for 3-D coders, which is sufficiently larger than for component-wise compression and lossless coding.

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Proceedings Article | 25 February 2014 Paper

Metric performance in similar blocks search and their use in collaborative 3D filtering of grayscale images

Aleksey Rubel, Vladimir Lukin, Karen Egiazarian

Proceedings Volume 9019, 901909 (2014) https://doi.org/10.1117/12.2039247

KEYWORDS: Image filtering, Image processing, Denoising, 3D image processing, Image denoising, Mahalanobis distance, Data processing, Databases, Video, Visualization

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Proceedings Article | 17 October 2013 Paper

VST-based lossy compression of hyperspectral data for new generation sensors

Alexander Zemliachenko, Ruslan Kozhemiakin, Mykhail Uss, Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi

Proceedings Volume 8892, 88920L (2013) https://doi.org/10.1117/12.2028415

KEYWORDS: Image compression, Chromium, Interference (communication), Data compression, Sensors, Hyperspectral imaging, Data acquisition, Image filtering, Control systems, Remote sensing

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Proceedings Article | 19 February 2013 Paper

Visual quality analysis for images degraded by different types of noise

Nikolay Ponomarenko, Vladimir Lukin, Oleg Ieremeyev, Karen Egiazarian, Jaakko Astola

Proceedings Volume 8655, 86550E (2013) https://doi.org/10.1117/12.2000062

KEYWORDS: Visualization, Image quality, Databases, Interference (communication), Molybdenum, Visual analytics, Image analysis, Image visualization, Image processing, Image compression

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SPIE Journal Paper | 1 February 2013 Open Access

Image informative maps for component-wise estimating parameters of signal-dependent noise

Mikhail Uss, Benoit Vozel, Vladimir Lukin, Kacem Chehdi

JEI, Vol. 22, Issue 01, 013019, (February 2013) https://doi.org/10.1117/12.10.1117/1.JEI.22.1.013019

KEYWORDS: Interference (communication), Databases, Image processing, Statistical analysis, Calibration, Sensors, Image analysis, CCD image sensors, Volume rendering, Cameras

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SPIE Journal Paper | 13 December 2012 Open Access

Wiener discrete cosine transform-based image filtering

Oleksiy Pogrebnyak, Vladimir Lukin

JEI, Vol. 21, Issue 4, 043020, (December 2012) https://doi.org/10.1117/12.10.1117/1.JEI.21.4.043020

KEYWORDS: Image filtering, Electronic filtering, Filtering (signal processing), Image processing, Denoising, Bridges, Optical filters, Interference (communication), Image quality, Linear filtering

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SPIE Journal Paper | 28 June 2012

Maximum likelihood estimation of spatially correlated signal-dependent noise in hyperspectral images

Mikhail Uss, Benoit Vozel, Kacem Chehdi, Vladimir Lukin

OE, Vol. 51, Issue 11, 111712, (June 2012) https://doi.org/10.1117/12.10.1117/1.OE.51.11.111712

KEYWORDS: Interference (communication), Hyperspectral imaging, Sensors, 3D modeling, Correlation function, 3D image processing, Image processing, Signal to noise ratio, Data modeling, Motion models

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Proceedings Article | 2 February 2012 Paper

Sharpness metric for no-reference image visual quality assessment

Nikolay Ponomarenko, Vladimir Lukin, Oleg Eremeev, Karen Egiazarian, Jaakko Astola

Proceedings Volume 8295, 829519 (2012) https://doi.org/10.1117/12.906393

KEYWORDS: Image processing, Photography, Image analysis, Discrete wavelet transforms, Databases, Molybdenum, Image compression, Image visualization, Visualization, Image quality

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Proceedings Article | 2 February 2012 Paper

Performance evaluation for 2D and 3D filtering methods of noise removal in color images

Nikolay Ponomarenko, Vladimir Lukin, Alexander Zelensky, Karen Egiazarian, Jaakko Astola

Proceedings Volume 8295, 829506 (2012) https://doi.org/10.1117/12.906379

KEYWORDS: Image filtering, Optical filters, 3D image processing, Visualization, Image quality, Image processing, Digital filtering, Nonlinear filtering, Denoising, Databases

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Proceedings Article | 27 October 2011 Paper

Performance evaluation for blind methods of noise characteristic estimation for TerraSAR-X images

Vladimir Lukin, Sergey Abramov, Dmitriy Fevralev, Nikolay Ponomarenko, Karen Egiazarian, Jaakko Astola, Benoit Vozel, Kacem Chehdi

Proceedings Volume 8180, 81800X (2011) https://doi.org/10.1117/12.897730

KEYWORDS: Speckle, Synthetic aperture radar, Image analysis, Error analysis, Statistical analysis, Image filtering, Image processing, Image segmentation, Edge detection, Image compression

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Proceedings Article | 4 February 2011 Paper

Color image lossy compression based on blind evaluation and prediction of noise characteristics

Nikolay Ponomarenko, Vladimir Lukin, Karen Egiazarian, Leena Lepisto

Proceedings Volume 7870, 78700S (2011) https://doi.org/10.1117/12.872009

KEYWORDS: Image compression, Image quality, Visualization, Image analysis, Chromium, Digital cameras, Quantization, Visual compression, Image processing, Molybdenum

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Proceedings Article | 4 February 2011 Paper

Efficiency analysis of DCT-based filters for color image database

Dmitriy Fevralev, Nikolay Ponomarenko, Vladimir Lukin, Sergey Abramov, Karen Egiazarian, Jaakko Astola

Proceedings Volume 7870, 78700R (2011) https://doi.org/10.1117/12.871944

KEYWORDS: Image filtering, Optical filters, Visualization, Databases, Image quality, Image processing, Denoising, Image visualization, Analytical research, Color image processing

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Images formed by different systems are often noisy which makes filtering a typical operation of image pre-processing. In many research papers, filter performance is analyzed for a limited number of standard test images and noise variances. Here we use a recently created color image database TID2008 that allows assessing filter efficiency for 25 color images corrupted by noise with different values of variance, both i.i.d. and spatially correlated. Besides, this image database serves the purpose of evaluating different quality metrics including those able to characterize visual quality of original and processed images considerably better than conventional MSE and PSNR. The study is carried out for filters based on discrete cosine transform (DCT) able to suppress both i.i.d. and spatially correlated noise depending upon a way of threshold setting. It is shown that improvement of PSNR (IPSNR) due to filtering is very close for R, G, and B components of color images and this improvement depends on image content. IPSNR reaches 9 dB for quite simple images and it is only about 1 dB for highly textural images if initial PSNR=30 dB. Note that IPSNR is larger if the original PSNR is smaller. The visual quality metric PSNR-HVS-M is studied as well. The metric PSNR-HVS-M becomes larger due to filtering but in smaller degree than PSNR does. We demonstrate that it is possible to forecast whether or not visual quality can be improved due to filtering or to detect in advance highly textural images for which filtering can be not efficient enough. The provided output MSEs are also compared to potential limits calculated according to the recently proposed methodology. It is demonstrated that for highly textural images the DCT filtering with 8x8 full overlapping blocks and hard thresholding provides output MSE close to potential limits. The provided and limit MSEs differ from each other by about 10%. For simpler images, the provided and limit MSEs can differ by 1.5...2.5 times. Analysis is also carried out for spatially correlated noise. It is shown that efficiency of filtering in this case is lower.

SPIE Journal Paper | 1 January 2011

Methods and automatic procedures for processing images based on blind evaluation of noise type and characteristics

Vladimir Lukin, Sergey Abramov, Nikolay Ponomarenko, Mikhail Uss, Mikhail Zriakhov, Benoit Vozel, Kacem Chehdi, Jaakko Astola

JARS, Vol. 5, Issue 1, 053502, (January 2011) https://doi.org/10.1117/12.10.1117/1.3539768

KEYWORDS: Image processing, Image compression, Image filtering, Interference (communication), Sensors, Lab on a chip, Edge detection, Chromium, Digital filtering, Remote sensing

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Proceedings Article | 23 October 2010 Paper

Classification of filtered multichannel images

Dmitriy Fevralev, Vladimir Lukin, Nikolay Ponomarenko, Benoit Vozel, Kacem Chehdi, Andriy Kurekin, Lik-Kwan Shark

Proceedings Volume 7830, 78300M (2010) https://doi.org/10.1117/12.864215

KEYWORDS: Image filtering, Image classification, Remote sensing, 3D image processing, Linear filtering, Visualization, Filtering (signal processing), Denoising, Landsat, Earth observing sensors

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SPIE Journal Paper | 1 April 2010 Open Access

Discrete cosine transform−based local adaptive filtering of images corrupted by nonstationary noise

Vladimir Lukin, Dmitriy Fevralev, Nikolay Ponomarenko, Sergey Abramov, Oleksiy Pogrebnyak, Karen Egiazarian, Jaakko Astola

JEI, Vol. 19, Issue 02, 023007, (April 2010) https://doi.org/10.1117/12.10.1117/1.3421973

KEYWORDS: Image filtering, Digital filtering, Nonlinear filtering, Image processing, Interference (communication), Radar, Electronic filtering, Visualization, Statistical analysis, Denoising

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Proceedings Article | 8 February 2010 Paper

A method for blind estimation of spatially correlated noise characteristics

Nikolay Ponomarenko, Vladimir Lukin, Karen Egiazarian, Jaakko Astola

Proceedings Volume 7532, 753208 (2010) https://doi.org/10.1117/12.847986

KEYWORDS: Image filtering, Image quality, Image processing, Image analysis, Visualization, Remote sensing, Denoising, Gaussian filters, Image sensors, Imaging systems

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Proceedings Article | 28 September 2009 Paper

Processing of images based on blind evaluation of noise type and characteristics

Vladimir Lukin, Sergey Abramov, Nikolay Ponomarenko, Mikhail Uss, Benoit Vozel, Kacem Chehdi, Jaakko Astola

Proceedings Volume 7477, 74770B (2009) https://doi.org/10.1117/12.830058

KEYWORDS: Image compression, Image filtering, Image processing, Sensors, Edge detection, Statistical analysis, Lab on a chip, Error analysis, Interference (communication), Digital filtering

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Proceedings Article | 11 February 2009 Paper

Local adaptive filtering of images corrupted by nonstationary noise

Vladimir Lukin, Dmitriy Fevralev, Nikolay Ponomarenko, Oleksiy Pogrebnyak, Karen Egiazarian, Jaakko Astola

Proceedings Volume 7245, 724506 (2009) https://doi.org/10.1117/12.805298

KEYWORDS: Image filtering, Digital filtering, Image processing, Radar, Filtering (signal processing), Nonlinear filtering, Visualization, Hyperspectral imaging, Imaging systems, Remote sensing

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Proceedings Article | 10 October 2008 Paper

Compression and classification of noisy multichannel remote sensing images

Vladimir Lukin, Nikolay Ponomarenko, Alexander Zelensky, Andriy Kurekin, Ken Lever

Proceedings Volume 7109, 71090W (2008) https://doi.org/10.1117/12.799497

KEYWORDS: Image compression, Remote sensing, Image classification, Chromium, Picosecond phenomena, Landsat, Data compression, JPEG2000, Control systems, Earth observing sensors

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Proceedings Article | 10 October 2008 Paper

Filtering of radar images based on blind evaluation of noise characteristics

Vladimir Lukin, Nikolay Ponomarenko, Sergey Abramov, Benoit Vozel, Kacem Chehdi, Jaakko Astola

Proceedings Volume 7109, 71090R (2008) https://doi.org/10.1117/12.799396

KEYWORDS: Image filtering, Radar, Image segmentation, Filtering (signal processing), Statistical analysis, Image processing, Error analysis, Lab on a chip, X band, Electronic filtering

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SPIE Journal Paper | 1 August 2008

Segmentation-based method for blind evaluation of noise variance in images

Sergey Abramov, Vladimir Lukin, Benoit Vozel, Kacem Chehdi, Jaakko Astola

JARS, Vol. 2, Issue 01, 023533, (August 2008) https://doi.org/10.1117/12.10.1117/1.2977788

KEYWORDS: Image segmentation, Remote sensing, Image processing, Krypton, Image filtering, Image analysis, Wavelets, Gallium, Statistical analysis, Synthetic aperture radar

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Proceedings Article | 3 March 2008 Paper

Adaptive DCT-based filtering of images corrupted by spatially correlated noise

Nikolay Ponomarenko, Vladimir Lukin, Aleksandr Zelensky, Jaakko Astola, Karen Egiazarian

Proceedings Volume 6812, 68120W (2008) https://doi.org/10.1117/12.764893

KEYWORDS: Image filtering, Digital filtering, Image processing, Denoising, Imaging systems, Optical filters, Nonlinear filtering, Visualization, Image denoising, Gaussian filters

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Proceedings Article | 26 February 2008 Paper

Image filter effectiveness characterization based on HVS

Vladimir Lukin, Nikolay Ponomarenko, Sergey Krivenko, Karen Egiazarian, Jaakko Astola

Proceedings Volume 6814, 68140Z (2008) https://doi.org/10.1117/12.774716

KEYWORDS: Image filtering, Image quality, Image processing, Digital filtering, Visualization, Image visualization, Nonlinear filtering, Optical filters, Image analysis, Image quality standards

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Proceedings Article | 24 October 2007 Paper

Improved minimal inter-quantile distance method for blind estimation of noise variance in images

Vladimir Lukin, Sergey Abramov, Alexander Zelensky, Jaakko Astola, Benoit Vozel, Kacem Chehdi

Proceedings Volume 6748, 67481I (2007) https://doi.org/10.1117/12.738006

KEYWORDS: Image segmentation, Remote sensing, Niobium, Data modeling, Statistical analysis, Image processing, Image analysis, Image filtering, Data processing, Error analysis

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Proceedings Article | 28 February 2007 Paper

Compression of noisy Bayer pattern color filter array images

Vladimir Lukin, Nikolay Ponomarenko, Andriy Bazhyna, Karen Egiazarian

Proceedings Volume 6498, 64980K (2007) https://doi.org/10.1117/12.715588

KEYWORDS: Image compression, Denoising, Chromium, Image processing, Quantization, Image quality, Digital cameras, Cameras, Optical filters, JPEG2000

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Proceedings Article | 27 February 2007 Paper

Object classification, segmentation, and parameter estimation in multichannel images by classifier learning with clustering of local parameters

Vladimir Lukin, Nikolay Ponomarenko, Alexander Zelensky, Karen Egiazarian, Jaakko Astola

Proceedings Volume 6497, 649712 (2007) https://doi.org/10.1117/12.705143

KEYWORDS: Image segmentation, Image classification, Image filtering, RGB color model, Optical filters, Image processing, Image analysis, Digital filtering, Nonlinear filtering, Quantitative analysis

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Proceedings Article | 29 September 2006 Paper

Quasi-optimal compression of noisy optical and radar images

Vladimir Lukin, Nikolay Ponomarenko, Mikhail Zriakhov, Alexander Zelensky, Karen Egiazarian, Jaakko Astola

Proceedings Volume 6365, 63650N (2006) https://doi.org/10.1117/12.689557

KEYWORDS: Image compression, Chromium, Remote sensing, Radar, JPEG2000, Lab on a chip, Image filtering, Data compression, Denoising, Data communications

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Proceedings Article | 25 August 2006 Paper

Use of minimal inter-quantile distance estimation in image processing

Vladimir Lukin, Sergey Abramov, Alexander Zelensky, Jaakko Astola

Proceedings Volume 6315, 63150O (2006) https://doi.org/10.1117/12.678764

KEYWORDS: Niobium, Image analysis, Remote sensing, Statistical analysis, Data modeling, Image processing, Mathematical modeling, Radar, Numerical simulations, Data processing

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Proceedings Article | 19 October 2005 Paper

A method for blind automatic evaluation of noise variance in images based on bootstrap and myriad operations

Vladimir Lukin, Sergey Abramov, Benoit Vozel, Kacem Chehdi

Proceedings Volume 5982, 59820Y (2005) https://doi.org/10.1117/12.626446

KEYWORDS: Statistical analysis, Remote sensing, Image processing, Niobium, Image analysis, Filtering (signal processing), Error analysis, Electroluminescence, Numerical simulations, Image filtering

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Proceedings Article | 30 August 2005 Paper

Myriad-based shift parameter estimation method and its application to image filtering and processing

Vladimir Lukin, Sergey Abramov, Alexander Zelensky, Jaakko Astola

Proceedings Volume 5916, 591601 (2005) https://doi.org/10.1117/12.614829

KEYWORDS: Statistical analysis, Image filtering, Digital filtering, Nonlinear filtering, Nano opto mechanical systems, Image processing, Filtering (signal processing), Data modeling, Optical filters, Statistical modeling

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Proceedings Article | 25 May 2005 Paper

Mitigation of image impairments for multichannel remote sensing data fusion

Andriy Kurekin, Alexander Dolia, David Marshall, Vladimir Lukin, Kenneth Lever

Proceedings Volume 5817, (2005) https://doi.org/10.1117/12.603103

KEYWORDS: Image fusion, Image processing, Image classification, Sensors, Image sensors, Image filtering, Image segmentation, Data fusion, Impairment mitigation, Remote sensing

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Proceedings Article | 1 March 2005 Paper

Locally adaptive image filtering based on learning with clustering

Nikolay Ponomarenko, Vladimir Lukin, Alexander Zelensky, Karen Egiazarian, Jaakko Astola

Proceedings Volume 5672, (2005) https://doi.org/10.1117/12.583222

KEYWORDS: Image filtering, Digital filtering, Image processing, Optical filters, Nonlinear filtering, Radar, Filtering (signal processing), Remote sensing, Image denoising, Numerical simulations

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Proceedings Article | 28 May 2004 Paper

Robust Lee local statistic filter for removal of mixed multiplicative and impulse noise

Nikolay Ponomarenko, Vladimir Lukin, Karen Egiazarian, Jaakko Astola

Proceedings Volume 5298, (2004) https://doi.org/10.1117/12.529123

KEYWORDS: Image filtering, Digital filtering, Optical filters, Image processing, Filtering (signal processing), Speckle, Nonlinear filtering, Finite impulse response filters, Numerical simulations, Imaging systems

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Proceedings Article | 5 February 2004 Paper

Image processing with texture feature preservation by three-state locally adaptive filter

Vladimir Lukin, Oleg Tsymbal, Nikolay Ponomarenko, Karen Egiazarian, Jaakko Astola

Proceedings Volume 5238, (2004) https://doi.org/10.1117/12.511518

KEYWORDS: Digital filtering, Image filtering, Image processing, Filtering (signal processing), Radar, Optical filters, Switching, Statistical analysis, Remote sensing, Compound parabolic concentrators

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Proceedings Article | 14 August 2003 Paper

Robust ground control point-matching algorithm for multichannel radar image geometric correction

Gennady Kulemin, Andrei Kurekin, Alexander Zelensky, Vladimir Lukin

Proceedings Volume 5097, (2003) https://doi.org/10.1117/12.487981

KEYWORDS: Radar, Image registration, Error analysis, Affine motion model, Image processing, Remote sensing, Algorithm development, Statistical analysis, Computer simulations, Performance modeling

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Proceedings Article | 28 May 2003 Paper

Blind evaluation of additive noise variance in textured images by nonlinear processing of block DCT coefficients

Nikolay Ponomarenko, Vladimir Lukin, Sergey Abramov, Karen Egiazarian, Jaakko Astola

Proceedings Volume 5014, (2003) https://doi.org/10.1117/12.477717

KEYWORDS: Image processing, Statistical analysis, Lab on a chip, Image analysis, Niobium, Spatial frequencies, Analog electronics, Numerical simulations, Interference (communication), Signal processing

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Proceedings Article | 7 March 2003 Paper

Automated robust procedure for SAR image filtering and preliminary analysis

Vladimir Lukin, Nikolay Ponomarenko, Sergey Abramov, Karen Egiazarian, Jaakko Astola

Proceedings Volume 4883, (2003) https://doi.org/10.1117/12.463075

KEYWORDS: Image filtering, Speckle, Image processing, Synthetic aperture radar, Digital filtering, Optical filters, Radar, Image analysis, Statistical analysis, Finite impulse response filters

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Proceedings Article | 22 May 2002 Paper

Blind evaluation of noise variance in images using myriad operation

Sergey Abramov, Vladimir Lukin, Alexander Zelensky, Jaakko Astola

Proceedings Volume 4667, (2002) https://doi.org/10.1117/12.467981

KEYWORDS: Error analysis, Statistical analysis, Image processing, Data modeling, Radar, Lab on a chip, Numerical simulations, Image analysis, Interference (communication), Image classification

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Proceedings Article | 22 May 2002 Paper

Digital elevation map reconstruction from isogram map using iterative DCT algorithm with nonlinear contraints

Nikolay Ponomarenko, Vladimir Lukin, Karen Egiazarian, Jaakko Astola

Proceedings Volume 4667, (2002) https://doi.org/10.1117/12.468002

KEYWORDS: Reconstruction algorithms, Image processing, Remote sensing, Digital filtering, Data communications, Linear filtering, Nonlinear filtering, Analytical research, Telecommunications, Signal attenuation

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Proceedings Article | 28 January 2002 Paper

Misclassification correction in primary local recognition of component images of multichannel remote sensing data

Antti Niemistoe, Vladimir Lukin, Alexander Dolia, Olli Yli-Harja, Ilya Shmulevich

Proceedings Volume 4541, (2002) https://doi.org/10.1117/12.454147

KEYWORDS: Image classification, Remote sensing, Radar, Image processing, Genetic algorithms, Optimization (mathematics), Digital filtering, Data modeling, Systems modeling, Signal processing

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Proceedings Article | 28 August 2001 Paper

Removing impulse bursts from images by training-based soft morphological filtering

Pertti Koivisto, Jaakko Astola, Vladimir Lukin, Vladimir Melnik, Oleg Tsymbal

Proceedings Volume 4388, (2001) https://doi.org/10.1117/12.438272

KEYWORDS: Image filtering, Radar, Filtering (signal processing), Digital filtering, Optimal filtering, Composites, Chromium, Remote sensing, Electronic filtering, Image analysis

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SPIE Journal Paper | 1 August 2001

Local activity indicators for hard-switching adaptive filtering of images with mixed noise

Vladimir Melnik, Vladimir Lukin, Alexander Zelensky, Jaakko Astola, Pauli Kuosmanen

OE, Vol. 40, Issue 08, (August 2001) https://doi.org/10.1117/12.10.1117/1.1385815

KEYWORDS: Digital filtering, Image filtering, Optical filters, Nonlinear filtering, Optical engineering, Image processing, Statistical analysis, Filtering (signal processing), Denoising, Numerical simulations

Proceedings Article | 8 May 2001 Paper

Two-stage radar image despeckling based on local statistic Lee and sigma filtering

Vladimir Lukin, Nikolay Ponomarenko, Leonid Alekseyev, Vladimir Melnik, Jaakko Astola

Proceedings Volume 4304, (2001) https://doi.org/10.1117/12.424967

KEYWORDS: Image filtering, Digital filtering, Radar, Speckle, Optical filters, Image processing, Synthetic aperture radar, Statistical analysis, Numerical simulations, Gaussian filters

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Proceedings Article | 8 May 2001 Paper

Local transform-based denoising for radar image processing

Karen Egiazarian, Vladimir Melnik, Vladimir Lukin, Jaakko Astola

Proceedings Volume 4304, (2001) https://doi.org/10.1117/12.424972

KEYWORDS: Denoising, Image filtering, Speckle, Radar, Digital filtering, Statistical analysis, Image processing, Numerical simulations, Synthetic aperture radar, Gaussian filters

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Proceedings Article | 4 April 2001 Paper

Neural networks for local recognition of images with mixed noise

Alexander Dolia, Vladimir Lukin, Alexander Zelensky, Jaakko Astola, Chris Anagnostopoulos

Proceedings Volume 4305, (2001) https://doi.org/10.1117/12.420932

KEYWORDS: Neural networks, Image processing, Digital filtering, Image filtering, Nonlinear filtering, Holmium, Image classification, Statistical analysis, Numerical simulations, Edge detection

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Proceedings Article | 23 January 2001 Paper

Evaluation of snow cover characteristics in Ukraine from the radar images of Ocean satellite

Gennady Kulemin, Vladimir Lukin, Alexander Zelensky, Leonid Alekseyev

Proceedings Volume 4171, (2001) https://doi.org/10.1117/12.413934

KEYWORDS: Radar, Remote sensing, Snow cover, Backscatter, Liquids, Crystals, Scattering, Satellites, Image filtering, Environmental sensing

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Proceedings Article | 19 January 2001 Paper

Correction of misclassifications in primary local image recognition using a nonlinear graph-based estimation technique

Vladimir Lukin, Ilya Shmulevich, Olli Yli-Harja, Alexander Dolia

Proceedings Volume 4170, (2001) https://doi.org/10.1117/12.413896

KEYWORDS: Image filtering, Digital filtering, Image classification, Filtering (signal processing), Neural networks, Radar, Multispectral imaging, Remote sensing, Statistical analysis, Signal processing

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Proceedings Article | 3 April 2000 Paper

Data fusion and processing for airborne multichannel system of radar remote sensing: methodology, stages, and algorithms

Vladimir Lukin, Jaakko Astola, Vladimir Melnik, Andrei Kurekin, Alexander Zelensky, Gennady Kulemin, Nikolay Ponomarenko, Alexander Dolia, Jussi Parkkinen

Proceedings Volume 4051, (2000) https://doi.org/10.1117/12.381634

KEYWORDS: Image filtering, Remote sensing, Digital filtering, Image processing, Radar, Data processing, Image classification, Optical filters, Ka band, Multichannel imaging systems

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Proceedings Article | 3 March 2000 Paper

Applications and properties of sigma and mean filters with adaptive window size

Nikolay Ponomarenko, Vladimir Lukin, Alexander Zelensky, Pertti Koivisto, Jaakko Astola

Proceedings Volume 3961, (2000) https://doi.org/10.1117/12.379402

KEYWORDS: Digital filtering, Image filtering, Optical filters, Medium wave, Radar, Image processing, Filtering (signal processing), Data processing, Linear filtering, Nonlinear filtering

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Proceedings Article | 3 March 2000 Paper

Use of homomorphic transforms in locally adaptive filtering of radar images

Vladimir Lukin, Vladimir Melnik, Victor Chemerovsky, Sari Peltonen, Pauli Kuosmanen

Proceedings Volume 3961, (2000) https://doi.org/10.1117/12.379391

KEYWORDS: Transform theory, Image filtering, Digital filtering, Image processing, Nonlinear filtering, Radar, Edge detection, Speckle, Synthetic aperture radar, Chromium

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Proceedings Article | 17 December 1999 Paper

Processing multichannel radar images by modified vector sigma filter for soil erosion degree determination

Andrei Kurekin, Vladimir Lukin, Alexander Zelensky, Oleg Tsymbal, Gennady Kulemin, Edwin Engman

Proceedings Volume 3868, (1999) https://doi.org/10.1117/12.373127

KEYWORDS: Image filtering, Image processing, Remote sensing, Radar, Digital filtering, Optical filters, Polarization, Image classification, Data processing, Visualization

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Proceedings Article | 18 October 1999 Paper

Modified vector sigma filter and its application to color and multichannel remote sensing radar image processing

Andrei Kurekin, Vladimir Lukin, Alexander Zelensky, Jaakko Astola, Pertti Koivisto

Proceedings Volume 3808, (1999) https://doi.org/10.1117/12.365854

KEYWORDS: Image filtering, Optical filters, Image processing, Digital filtering, Radar, Remote sensing, Image quality, RGB color model, Distance measurement, Gaussian filters

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Proceedings Article | 5 March 1999 Paper

Property analysis of noise-suppressing L-filters for speckle image processing

Vladimir Lukin, Vladimir Melnik, Victor Chemerovsky, Alexander Zelensky, Jaakko Astola, Pauli Kuosmanen, Heikki Huttunen

Proceedings Volume 3646, (1999) https://doi.org/10.1117/12.341083

KEYWORDS: Digital filtering, Image processing, Speckle, Statistical analysis, Image filtering, Contamination, Nonlinear filtering, Coherence imaging, Imaging systems, Monte Carlo methods

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Proceedings Article | 11 December 1998 Paper

Soil-erosion-state interpretation using pre- and postprocessing of multichannel radar images

Gennady Kulemin, Vladimir Lukin, Alexander Zelensky, Andrei Kurekin, Edwin Engman

Proceedings Volume 3499, (1998) https://doi.org/10.1117/12.332744

KEYWORDS: Image filtering, Radar, Remote sensing, Image processing, Data processing, Digital filtering, Data modeling, Neurons, Agriculture, Ka band

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Proceedings Article | 24 September 1998 Paper

Hard-switching adaptive filter for speckle image processing

Vladimir Lukin, Vladimir Melnik, Victor Chemerovsky, Jaakko Astola, Kari Saarinen

Proceedings Volume 3457, (1998) https://doi.org/10.1117/12.323454

KEYWORDS: Image filtering, Digital filtering, Image processing, Matrices, Linear filtering, Optical filters, Nonlinear filtering, Speckle, Synthetic aperture radar, Numerical simulations

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Proceedings Article | 6 April 1998 Paper

Adaptive alfa-trimmed filters for speckle image processing

Vladimir Lukin, Vladimir Melnik, Victor Chemerovsky, Jaakko Astola, Pauli Kuosmanen, Kari Saarinen

Proceedings Volume 3304, (1998) https://doi.org/10.1117/12.304601

KEYWORDS: Digital filtering, Image filtering, Speckle, Image processing, Optical filters, Nonlinear filtering, Sodium, Interference (communication), Filtering (signal processing), Synthetic aperture radar

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Proceedings Article | 6 April 1998 Paper

Nonlinear algorithms of isogram extraction from topographic maps

Vladimir Lukin, Nikolay Ponomarenko, Andrei Kurekin, Alexander Zelensky, Jaakko Astola, Pertti Koivisto, Kari Saarinen

Proceedings Volume 3304, (1998) https://doi.org/10.1117/12.304615

KEYWORDS: Digital filtering, Nonlinear filtering, Scanners, Optical filters, Vegetation, Feature extraction, Image processing, Binary data, Radar, RGB color model

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Proceedings Article | 30 December 1997 Paper

Radar dual-polarization remote sensing of soil erosion

Gennady Kulemin, Vladimir Lukin, Alexander Zelensky, Andrei Kurekin, Edwin Engman

Proceedings Volume 3222, (1997) https://doi.org/10.1117/12.298141

KEYWORDS: Radar, Remote sensing, Soil science, Polarization, Fractal analysis, Surface roughness, Agriculture, Image filtering, Image processing, In situ metrology

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Proceedings Article | 14 October 1997 Paper

Adaptive-vector LQ filter for color image processing

Andrei Kurekin, Vladimir Lukin, Alexander Zelensky, Jaakko Astola, Pauli Kuosmanen, Kari Saarinen

Proceedings Volume 3167, (1997) https://doi.org/10.1117/12.279649

KEYWORDS: Image filtering, Optical filters, Digital filtering, Color image processing, Image processing, Analog electronics, Denoising, Computer simulations

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SPIE Journal Paper | 1 October 1997

Nonlinear locally adaptive and iterative algorithms of image restoration

Vladimir Melnik, Vladimir Lukin, Alexander Zelensky, Heikki Huttunen, Jaakko Astola

JEI, Vol. 6, Issue 04, (October 1997) https://doi.org/10.1117/12.10.1117/12.276851

KEYWORDS: Image filtering, Digital filtering, Nonlinear filtering, Image restoration, Reconstruction algorithms, Filtering (signal processing), Image processing, Electronic filtering, Image quality, Image enhancement

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Proceedings Article | 19 September 1997 Paper

Adaptive nonlinear vector filtering of multichannel radar images

Vladimir Lukin, Alexander Zelensky, Andrei Kurekin, Jaakko Astola, Kari Saarinen

Proceedings Volume 3119, (1997) https://doi.org/10.1117/12.285553

KEYWORDS: Image filtering, Digital filtering, Radar, Image processing, Nonlinear filtering, Optical filters, Remote sensing, Filtering (signal processing), Synthetic aperture radar, Radar signal processing

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Proceedings Article | 4 April 1997 Paper

Adaptive nonlinear L2 and L3 filters for speckled image processing

Vladimir Lukin, Vladimir Melnik, Victor Chemerovsky, Jaakko Astola

Proceedings Volume 3026, (1997) https://doi.org/10.1117/12.271139

KEYWORDS: Speckle, Digital filtering, Image filtering, Nonlinear filtering, Image processing, Filtering (signal processing), Optical filters, Statistical analysis, Ultrasonography, Medical imaging

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Proceedings Article | 8 October 1996 Paper

Nonlinear locally adaptive and iterative algorithms of image restoration

Vladimir Melnik, Vladimir Lukin, Alexander Zelensky, Heikki Huttunen, Jaakko Astola

Proceedings Volume 2823, (1996) https://doi.org/10.1117/12.253451

KEYWORDS: Digital filtering, Image restoration, Nonlinear filtering, Image filtering, Electronic filtering, Filtering (signal processing), Image processing, Image quality, Quantization, Reconstruction algorithms

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SPIE Journal Paper | 1 July 1996

Digital adaptive robust algorithms for radar image filtering

Vladimir Lukin, Vladimir Melnik, Oleksiy Pogrebnyak, Alexander Zelensky, Jaakko Astola, Kari Saarinen

JEI, Vol. 5, Issue 03, (July 1996) https://doi.org/10.1117/12.10.1117/12.240715

KEYWORDS: Digital filtering, Image filtering, Radar, Image processing, Speckle, Filtering (signal processing), Linear filtering, Digital image processing, Image quality, Nonlinear filtering

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Proceedings Article | 25 March 1996 Paper

Algorithms of image nonlinear adaptive filtering using fragment recognition by expert system

Vladimir Lukin, Nikolay Ponomarenko, Jaakko Astola, Kari Saarinen

Proceedings Volume 2662, (1996) https://doi.org/10.1117/12.235830

KEYWORDS: Digital filtering, Optical filters, Image filtering, Linear filtering, Image processing, Detection and tracking algorithms, Nonlinear filtering, Finite impulse response filters, Complex systems, Statistical analysis

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Proceedings Article | 19 January 1996 Paper

Soil characteristics estimation from multispectral and multipolarization radar remote-sensing data

Gennady Kulemin, Andrei Kurekin, Vladimir Lukin, Alexander Zelensky

Proceedings Volume 2599, (1996) https://doi.org/10.1117/12.230400

KEYWORDS: Radar, Remote sensing, Soil science, Dielectrics, Image filtering, Surface roughness, Image processing, Sensing systems, In situ metrology, Agriculture

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Proceedings Article | 24 November 1995 Paper

Image enhancement using signal spectral abundance

Andrei Kurekin, Vladimir Lukin, Irina Lukina, Alexander Zelensky

Proceedings Volume 2585, (1995) https://doi.org/10.1117/12.227201

KEYWORDS: Imaging systems, Antennas, Image processing, Digital image processing, Image enhancement, Signal processing, Signal to noise ratio, Acoustics, Image quality, Image resolution

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Proceedings Article | 24 November 1995 Paper

Soil moisture and erosion degree estimation from multichannel microwave remote sensing data

Gennady Kulemin, Andrei Kurekin, Vladimir Lukin, Alexander Zelensky

Proceedings Volume 2585, (1995) https://doi.org/10.1117/12.227178

KEYWORDS: Soil science, Radar, Remote sensing, Dielectrics, Polarization, Dielectric polarization, In situ metrology, Surface roughness, Microwave radiation, Fractal analysis

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Proceedings Article | 5 June 1995 Paper

Fast-data-weighting algorithms of nonfocused SAR-image forming

Igor Anukhin, Vladimir Lukin, Alexander Zelensky

Proceedings Volume 2487, (1995) https://doi.org/10.1117/12.210854

KEYWORDS: Synthetic aperture radar, Data processing, Radar, Holograms, Lawrencium, Antennas, Signal processing, Image resolution, Phase compensation, Image enhancement

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Proceedings Article | 28 March 1995 Paper

Application of order statistic filtering to multichannel radar image processing

Vladimir Lukin, Andrei Kurekin, Vladimir Melnik, Alexander Zelensky

Proceedings Volume 2424, (1995) https://doi.org/10.1117/12.205232

KEYWORDS: Digital filtering, Image filtering, Image processing, Radar, Data processing, Optical filters, Remote sensing, Synthetic aperture radar, Speckle, Image processing algorithms and systems

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