Prof. Youcef Smara Profile

Prof. Youcef Smara

at USTHB

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Author

Publications (5)

SPIE Journal Paper | 28 August 2021

Panchromatic and multispectral image fusion using the spatial frequency and the à trous wavelet transform

Samia Massout, Youcef Smara

JARS, Vol. 15, Issue 03, 036510, (August 2021) https://doi.org/10.1117/12.10.1117/1.JRS.15.036510

KEYWORDS: Image fusion, Spatial frequencies, Spatial resolution, Wavelet transforms, Multispectral imaging, Discrete wavelet transforms, Satellites, Image quality, Satellite imaging, Image processing

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SPIE Journal Paper | 25 April 2019

Polarimetric synthetic aperture radar speckle filtering by multiscale edge detection

Souhila Boutarfa, Lynda Bouchemakh, Youcef Smara

JARS, Vol. 13, Issue 02, 024507, (April 2019) https://doi.org/10.1117/12.10.1117/1.JRS.13.024507

KEYWORDS: Image filtering, Polarimetry, Speckle, Wavelets, Synthetic aperture radar, Principal component analysis, Digital filtering, Linear filtering, Edge detection, Scattering

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Proceedings Article | 10 October 2018 Paper

Phytoplankton initiation bloom magnitude in Algerian continental shelf waters using 11 years of ocean color observations

S. Benzouai, F. Louanchi, Y. Smara

Proceedings Volume 10784, 1078413 (2018) https://doi.org/10.1117/12.2325442

KEYWORDS: Electroluminescence, Water, Earth observing sensors, Meteorology, Ecosystems, Biological research

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Phytoplankton are photosynthetic organisms that live in the upper part of the water's surface. A rapid growth in a short time cause the appearance of blooms which can long-term impact marine ecosystem and fisheries. Chlorophyll-a (chl-a) concentrations, the proxy pigment of phytoplankton biomass, is measured with conventional in-situ analysis methods and retrieved from satellite observations. Currently, remotely sensed ocean color data constitute a rich and important spatiotemporal database that has been exploited in many scientific studies and has been shown to be relevant in phytoplankton dynamic metrics. Here in this study, we analyze 11 years of ocean color observations, MERIS (2003-2012) and MODIS (2012-2013) archives, over Algerian coasts in order to compute the chl-a concentrations corresponding to the start and end of bloom event. The determination is based on one of the most used definition of bloom in pelagic ocean, when chl-a concentrations rise above and fall below the full time series median for each pixel plus 5%. Satellite data were preprocessed considering flags to eliminate contaminated pixels, land, cloud and open water pixels. Spatial distribution mapping of results was done showing that the highest magnitudes are concentrated near the coasts. For statistical comparison purpose, the shelf waters were divided into six regions, limited from north by the 1000 m bathymetric curve and from south by Algerian coastline. The east and west limits for each region are chosen considering the marine meteorological regions. This study highlights for the first time the spatial distribution, at high resolution (250 m), of bloom initiation magnitudes along Algerian shelf waters, taking into account the influence of important wadis (small Mediterranean river) flowing there, the marine meteorology and north Algeria pluviometry. Statistics, particularly means, based on the proposed regions, seems to be relevant because they are consistent with the dominant regional pluviometry. In fact, the precipitation causes a runoff of the lands and this flow enters the sea loaded with nutrients. The obtained values can be used to determine the bloom start timing and others phenological parameters.

SPIE Journal Paper | 15 August 2018

Denoising polarimetric radar images using constant false alarm detectors

Lynda Bouchemakh, Youcef Smara

JARS, Vol. 12, Issue 03, 035012, (August 2018) https://doi.org/10.1117/12.10.1117/1.JRS.12.035012

KEYWORDS: Polarimetry, Image filtering, Sensors, Speckle, Target detection, Radar, Synthetic aperture radar, Denoising, Lithium, Image processing

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Proceedings Article | 24 October 2011 Paper

Improvement of PWF filter using wavelet thresholding for polarimetric SAR imagery

S. Boutarfa, Y. Smara, H. Fadel, N. Bouguessa

Proceedings Volume 8286, 82860Y (2011) https://doi.org/10.1117/12.912757

KEYWORDS: Image filtering, Polarimetry, Wavelets, Synthetic aperture radar, Speckle, Target detection, Edge detection, Stationary wavelet transform, Image segmentation, Radar

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