Presentation + Paper
20 September 2016 Inverse synthetic aperture LADAR image construction: an inverse model-based approach
Author Affiliations +
Abstract
Standard Synthetic Aperture LADAR (SAL) image processing techniques use fast Fourier transforms (FFTs) to render images. This leads to noise amplification and estimates of the complex-valued reflection coefficient, thus resulting in high variation known as speckle. In this paper we propose a model-based iterative reconstruction (MBIR) approach using a Bayesian framework to form SAL images. The resulting images are the maximum a posteriori (MAP) estimate of object's real-valued surface reflectance. To overcome the complexity of the MAP cost function, we use the expectation maximization (EM) algorithm to derive a surrogate function which is then optimized. The proposed algorithm is tested on simulated data and compared against the Fourier-based approach.
Conference Presentation
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Casey J. Pellizzari and Charles A. Bouman "Inverse synthetic aperture LADAR image construction: an inverse model-based approach", Proc. SPIE 9982, Unconventional Imaging and Wavefront Sensing XII, 99820F (20 September 2016); https://doi.org/10.1117/12.2236133
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CITATIONS
Cited by 1 scholarly publication and 1 patent.
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KEYWORDS
Expectation maximization algorithms

Image processing

Model-based design

LIDAR

Signal to noise ratio

Speckle

Reconstruction algorithms

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