Vector quantization and signal compression
Vector quantization and signal compression
An evolutionary technique based on K-means algorithm for optimal clustering in RN
Information Sciences—Applications: An International Journal
An improved algorithm for clustering gene expression data
Bioinformatics
Embedded zerotree wavelets coding based on adaptive fuzzy clustering for image compression
Image and Vision Computing
Automatic Clustering Using an Improved Differential Evolution Algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A fast exact GLA based on code vector activity detection
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure
IEEE Transactions on Image Processing
Hierarchical Dynamic Range Coding of Wavelet Subbands for Fast and Efficient Image Decompression
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Rate Bounds on SSIM Index of Quantized Images
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
In search of optimal centroids on data clustering using a binary search algorithm
Pattern Recognition Letters
Black hole: A new heuristic optimization approach for data clustering
Information Sciences: an International Journal
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Taking both the correlations among and within wavelet subbands of images into account, in this paper we proposed an evolutionary clustering based vector quantization (VQ) and set partitioning in hierarchical trees (SPIHT) coding method for image compression. One-step gradient descent genetic algorithm (OSGD-GA) is designed for optimizing the codebooks of the low-frequency wavelet coefficient by defining the importance degree of each coefficient and utilizing fuzzy membership to address the automatic clustering. This new VQ technology exploits the global searching capability of OSGD-GA and can automatically obtain contextual constraints on membership condition by weighted average method of the importance, so it can overcome the drawbacks of classical clustering algorithm. Then the scalar quantization followed by SPIHT coding algorithm is employed for the high-frequency wavelet coefficients. Some simulational experiments are taken to investigate the performance of the proposed method. The results show that our proposed method not only brings about some new ideas in combining the evolutionary clustering based VQ and SPIHT coding, but also yields an improvement of PSNR to the greatest 0.66dB over SPIHT algorithm.