Speckle reduction of SAR images using neural networks

David Blacknell; Christopher John Oliver; Martin Warner

doi:10.1117/12.227161

21 November 1995 Speckle reduction of SAR images using neural networks

David Blacknell, Christopher John Oliver, Martin Warner

Proceedings Volume 2584, Synthetic Aperture Radar and Passive Microwave Sensing; (1995) https://doi.org/10.1117/12.227161
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

Given a high-quality, distortion free SAR image generated by a SAR processor, we would like to remove the speckle to reveal the underlying cross-section. Traditional filter-based techniques all suffer from the fact that the large filter size required for effective smoothing will cover a highly inhomogeneous region. A CPU intensive algorithmic noise removal process called simulated annealing has been successfully applied to both SAR intensity images and SAR texture images generated using a mean-normalized log texture estimator. To improve the execution time of the smoothing process, we have adopted a neural network based solution which emulates simulated annealing. A factorized neural network was chosen, consisting of a vector-quantizer first stage which is used to select a specific multi-layer perceptron from the second stage. This technique reduces both the training and run times for large neural networks. A further reduction in training times is achieved by the use of self-adjusting training algorithms. Statistical analysis of test data has shown that the network produces a good approximation to the estimated cross-section. Simulated annealing has the advantage of a much larger adaptive input window than the neural network, and a better comparison can be made by restricting simulated annealing to operate on a window with dimensions comparable with that of the neural network. A comparison with alternative techniques based on multi- dimensional lookup tables is also presented, comparing both the quality of the result with the execution time of the algorithm.

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David Blacknell, Christopher John Oliver, and Martin Warner "Speckle reduction of SAR images using neural networks", Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); https://doi.org/10.1117/12.227161

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KEYWORDS

Synthetic aperture radar

Neural networks

Algorithms

Image processing

Speckle

Statistical analysis

Distortion

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