Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Efficient Context-Based Entropy Coding Lossy Wavelet Image Compression
DCC '97 Proceedings of the Conference on Data Compression
Context Quantization with Fisher Discriminant for Adaptive Embedded Wavelet Image Coding
DCC '99 Proceedings of the Conference on Data Compression
Context Modeling and Entropy Coding of Wavelet Coefficients for Image Compression
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Embedded image coding using zerotrees of wavelet coefficients
IEEE Transactions on Signal Processing
A New Convergence Proof of Fuzzy c-Means
IEEE Transactions on Fuzzy Systems
Image subband coding using context-based classification and adaptive quantization
IEEE Transactions on Image Processing
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
Context-based entropy coding of block transform coefficients for image compression
IEEE Transactions on Image Processing
Efficient sign coding and estimation of zero-quantized coefficients in embedded wavelet image codecs
IEEE Transactions on Image Processing
Lossless image compression with projection-based and adaptive reversible integer wavelet transforms
IEEE Transactions on Image Processing
Embedded image compression based on wavelet pixel classification and sorting
IEEE Transactions on Image Processing
Adaptive prediction trees for image compression
IEEE Transactions on Image Processing
Adaptive downsampling to improve image compression at low bit rates
IEEE Transactions on Image Processing
On the Use of Context-Weighting in Lossless Bilevel 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
Evolutionary clustering based vector quantization and SPIHT coding for image compression
Pattern Recognition Letters
A learning based self-organized additive fuzzy clustering method and its application for EEG data
International Journal of Knowledge-based and Intelligent Engineering Systems - Intelligent Information Processing: Techniques and Applications
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In this paper, a new quantization approach based on an adaptive fuzzy c-means clustering for image compression is presented. The fuzzy cluster theory is applied to quantizing the wavelet coefficients of low-frequency subband after the image has been decomposed by wavelet transform. The method can automatically label the importance degree of coefficients of wavelets, and get new constraints on membership condition by weighted average method of the importance and 1 q"k=@q"k^(^1^).1+@q"k^(^2^).@l"k,@q"k^(^1^)+@q"k^(^2^)=1. Based on this condition, we cluster again. The proof of convergence of the algorithm is given. The experimental results show that exacter reconstructed values of wavelet coefficients can be obtained at low bit-rates, the subjective and objective quality of the reconstructed image is improved. This technique is shown to yield PSNR of reconstructed images improvement from 0.2dB to 2.8dB. This paper has brought about some new ideas in combining the fuzzy cluster algorithm with the embedded zerotree wavelets algorithm.