Journal of Algorithms
Discrete cosine transform: algorithms, advantages, applications
Discrete cosine transform: algorithms, advantages, applications
Vector quantization and signal compression
Vector quantization and signal compression
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
IEEE Transactions on Signal Processing
Variations on a theme by Huffman
IEEE Transactions on Information Theory
Predictive mean search algorithms for fast VQ encoding of images
IEEE Transactions on Consumer Electronics
Lossless compression of VQ index with search-order coding
IEEE Transactions on Image Processing
Region-based fractal image compression
IEEE Transactions on Image Processing
Fast full search equivalent encoding algorithms for image compression using vector quantization
IEEE Transactions on Image Processing
High-order entropy coding for images
IEEE Transactions on Circuits and Systems for Video Technology
New Bit Reduction of Vector Quantization Using Block Prediction and Relative Addressing
Fundamenta Informaticae
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The vector quantization (VQ) compression scheme has been well accepted as an efficient image compression technique. However, the compression bit rate of the VQ scheme is limited. In order to improve its efficiency, in this paper, we shall propose a new lossless data compression scheme to further condense the VQ index table. The proposed scheme exploits the inter-block correlations in the index table to re-encode the indices. Unlike the well known existing re-encoding schemes such as SOC and STC, the proposed scheme uses a smaller number of compression codes to encode every index that coincides with another on the predefined path. Compared with VQ, SOC and STC, the proposed scheme performs better in terms of compression bit rate.