Vector quantization and signal compression
Vector quantization and signal compression
Application of Principal Component Analysis to Multikey Searching
IEEE Transactions on Software Engineering
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
A new dynamic finite-state vector quantization algorithm for image compression
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
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A novel method for the compression of the index table of vector quantization (VQ) is proposed in this paper. This method is designed based on the observation that neighboring image blocks are highly correlated. In other words, VQ-encoded neighboring image blocks tend to have similar indices if the codebook used in VQ is previously sorted by the principal component analysis technique. According to this characteristic, we find the same or similar indices around the current processing index to process it. In addition, the pre-statistics technique is employed to gather differences that appear most often in the index table. Simulation results indicate that the newly proposed scheme achieves significant reduction of bit rate without losing any image quality by the original VQ encoding.