Compression of detected SAR imagery with JPEG 2000
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The wavelet-based JPEG 2000 image compression standard is flexible enough to handle a large number of imagery types in a broad range of applications. One important application is the use of JPEG 2000 to compress imagery collected by remote sensing systems. This general class of imagery is often larger -- in terms of number of pixels) -- than most other classes of imagery. Support for tiling and the embedded, progressively ordered bit stream of JPEG 2000 are very useful in handling very large images. However, the performance of JPEG 2000 on detected SAR (Synthetic Aperture Radar) and other kinds of specular imagery is not as good, from the perspective of visual image quality, as its performance on more 'literal' imagery types. In this paper, we try to characterize the problem by analyzing some statistical and qualitative differences between detected SAR and other more literal remote sensing imagery types. Several image examples are presented to illustrate the differences. JPEG 2000 is very flexible and offers a wider range of options that allow for technology that can be used to optimize the algorithm for a particular imagery type or application. A number of different JPEG 2000 options - - including subband, weighting, trellis-coded quantization (TCQ), and packet decomposition -- are explored for their impact to SAR image quality. Finally, the anatomy of a texture-preserving wavelet compression scheme is presented with very impressive visual results. The demonstration system used for this paper is currently not supported by the JPEG 2000 standard, but it is hoped that with additional research, a variant of the scheme can be fit into the framework of JPEG 2000.
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