Compression of SAR imagery for battlefield digitization is discussed in this paper. The images are first processed to separate out possible target areas. These target areas are compressed losslessly to avoid any degra...
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(纸本)0819424358
Compression of SAR imagery for battlefield digitization is discussed in this paper. The images are first processed to separate out possible target areas. These target areas are compressed losslessly to avoid any degradation of the images. The background information which is usually necessary to establish context, is compressed using a hybrid vectorquantization algorithm. An adaptive variable rate residualvector quantizer is used to compress the residual signal generated by a neural network predictor. The vector quantizer codebooks are optimized for entropy coding using an entropy-constrained algorithm to further improve the coding performance. This constrained vector-quantizer combination performs extremely well as suggested by the experimental results.
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