NYI: Vector Quantization Codebook Processing and Organization

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Riskin New ways to use Vector Quantization (VQ) other than strictly for data compression are being investigated, and are being applied to applications such as image processing, halftoning, progressive transmission, and immunity against communication channel noise. In many applications, both VQ and many image processing operations are applied to small subblocks of an image. The image processing step can be applied ahead of time to each vector in a VQ codebook, with the processed vectors stored along with the codebook. If the computational complexity of the VQ encoder is lower than that of the image processing step, this reduces the computational complexity. This approach is being applied to halftoning, edge detection, and histogram equalization. In a progressive transmission system, the received image is reconstructed as an increasingly better reproduction of the transmitted image as bits arrive. Ways to organize and order a VQ codebook so that it can be used for direct progressive transmission of full search VQ are being studied. In an ordered VQ, the VQ codeword index is correlated with the codeword location in the input space. This ordinal mapping feature of clustering codewords with similar indexes to obtain additional reproduction vectors for the decoder is being exploited. Extentions to progressive transmission of ordered VQ indexes over noisy communication channels are being included.