Structural image codebooks and the self-organizing feature map algorithm

摘要

The Kohonen self-organizing feature map algorithm is used to design hypercubically structured codebooks for memoryless vector quantization at a bit rate below 0.75 b/pixel for 512*512 monochrome still images. A decimated-search method that searches only a fraction of the codebook during both the training and the encoding processes is introduced. The effectiveness of the design is demonstrated by comparing the codebooks with those designed by the Linde-Buzo-Gray (LBG) algorithm. The coded images are seen to have similar objective and perceptual quality as those encoded by the LBG codebooks at a fraction of the search complexity.