Modified SPIHT encoding for SAR image data

TitleModified SPIHT encoding for SAR image data
Publication TypeConference Paper
Year of Publication1999
AuthorsZeng, Z., and I. Cumming
Conference NameData Compression Conference, 1999. Proceedings. DCC '99
Date Publishedmar.
Keywordsarithmetic codes, arithmetic coding, data compression, decomposition, image coding, image texture, interference suppression, lossless compression, modified SPIHT encoding, modified zero-tree coding, quadtree homogeneous decomposition, quadtrees, radar imaging, SAR image data, skewed distribution, soft-thresholding speckle reduction, speckle, subimage, synthetic aperture radar, transform coding, tree-structured texture analysis, tree-structured wavelet transform, wavelet transforms, wavelet-based image compression

Summary form only given. We developed a wavelet-based SAR image compression algorithm which combines tree-structured texture analysis, soft-thresholding speckle reduction, quadtree homogeneous decomposition, and a modified zero-tree coding scheme. First, the tree-structured wavelet transform is applied to the SAR image. The decomposition is no longer simply applied to the low-scale subsignals recursively but to the output of any filter. The measurement of the decomposition is the energy of the image. If the energy of a subimage is significantly smaller than others, we stop the decomposition in this region since it contains less information. The texture factors are created after this step, which represents the amount of texture information. Second, quadtree decomposition is used to split the components in the lowest scale component into two sets, a homogeneous set and a target set. The homogeneous set consists of the relatively homogeneous regions. The target set consists of those non-homogeneous regions which have been further decomposed into single component regions. A conventional soft-threshold is applied to reduce speckle noise on all the wavelet coefficients except those of the lowest scale. The feature factor is used to set the threshold. Finally, the conventional SPIHT methods are modified based on the result from the tree-structured decomposition and the quadtree decomposition. In the encoder, the amount of speckle reduction is chosen based on the requirements of the user. Different coding schemes are applied to the homogeneous set and the target set. The skewed distribution of the residuals makes arithmetic coding the best choice for lossless compression


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