Introduction to algorithms
Vector quantization and signal compression
Vector quantization and signal compression
Acceleration of Similarity-Based Partial Image Retrieval using Multistage Vector Quantization
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Efficient vector quantization using genetic algorithm
Neural Computing and Applications
K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector quantizers with direct sum codebooks
IEEE Transactions on Information Theory
A unified approach to tree-structured and multistage vector quantization for noisy channels
IEEE Transactions on Information Theory
IEEE Transactions on Consumer Electronics
Conditional entropy-constrained residual VQ with application to image coding
IEEE Transactions on Image Processing
Constrained-storage vector quantization with a universal codebook
IEEE Transactions on Image Processing
A fast PNN design algorithm for entropy-constrained residual vector quantization
IEEE Transactions on Image Processing
Multipurpose image watermarking algorithm based on multistage vector quantization
IEEE Transactions on Image Processing
Image coding using entropy-constrained residual vector quantization
IEEE Transactions on Image Processing
Improved batch fuzzy learning vector quantization for image compression
Information Sciences: an International Journal
Fuzzy declustering-based vector quantization
Pattern Recognition
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Multistage vector quantization (MSVQ) and their variants have been recently proposed. Before MSVQ is designed, the user must artificially determine the number of codewords in each VQ stage. However, the users usually have no idea regarding the number of codewords in each VQ stage, and thus doubt whether the resulting MSVQ is optimal. This paper proposes the genetic design (GD) algorithm to design the MSVQ. The GD algorithm can automatically find the number of codewords to optimize each VQ stage according to the rate-distortion performance. Thus, the MSVQ based on the GD algorithm, namely MSVQ(GD), is proposed here. Furthermore, using a sharing codebook (SC) can further reduce the storage size of MSVQ. Combining numerous similar codewords in the VQ stages of MSVQ produces the codewords of the sharing codebook. This paper proposes the genetic merge (GM) algorithm to design the SC of MSVQ. Therefore, the constrained-storage MSVQ using a SC, namely CSMSVQ, is proposed and outperforms other MSVQs in the experiments presented here.