Speckle filtering by wavelet analysis and synthesis

Katia Lebart; Jean-Marc Boucher

doi:10.1117/12.255275

23 October 1996 Speckle filtering by wavelet analysis and synthesis

Katia Lebart, Jean-Marc Boucher

Proceedings Volume 2825, Wavelet Applications in Signal and Image Processing IV; (1996) https://doi.org/10.1117/12.255275
Event: SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, 1996, Denver, CO, United States

Abstract

In speckled radar images, filtering must achieve a tradeoff between smoothing of homogeneous areas and edge and texture preservation. Multiscale analysis splits up the image information content, such as edges and texture, according to a scale factor by successive lowpass and highpass filterings followed by downsampling. The speckle noise is present on each downsampled image. Each image level is then filtered in order to reduce the speckle noise. High frequency images are processed by median filtering or spatial filtering, or by using a threshold. On low frequency images a distinction is made between homogeneous areas, textural areas and areas including edges according to the values of the variation coefficient. Each class is processed differently. A Wiener filter including a multiplicative noise hypothesis for the speckle is used for textured areas. For homogeneous areas the pixel value is simply replaced by the mean value. For areas containing edges, the pixel value is let unchanged. The filtered image is finally obtained y synthesis from these images. This algorithm has been applied to an ERS1 image.

Citation Download Citation

Katia Lebart and Jean-Marc Boucher "Speckle filtering by wavelet analysis and synthesis", Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996); https://doi.org/10.1117/12.255275

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