Vector quantization and signal compression
Vector quantization and signal compression
Ten lectures on wavelets
Image Wavelet Coding Systems: Part II of Set Partition Coding and Image Wavelet Coding Systems
Foundations and Trends in Signal Processing
Image and Vision Computing
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Variable-rate tree-structured VQ is applied to the coefficients obtained from an orthogonal wavelet decomposition. After encoding a vector, we examine the spatially corresponding vectors in the higher subbands to see whether or not they are "significant", that is, above some threshold. One bit of side information is sent to the decoder to inform it of the result. When the higher bands are encoded, those vectors which were earlier marked as insignificant are not coded. An improved version of the algorithm makes the decision not to code vectors from the higher bands based on a distortion/rate tradeoff rather than a strict thresholding criterion. Results of this method on the test image "Lena" yielded a PSNR of 30.15 dB at 0.174 bits per pixel.