Image Compression: A Survey <s> COMPRESSION BASED ON FUZZY ALGORITHMS <s> This paper presents the development and evaluation of fuzzy vector quantization algorithms. These algorithms are designed to achieve the quality of vector quantizers provided by sophisticated but computationally demanding approaches, while capturing the advantages of the frequently used in practice k-means algorithm, such as speed, simplicity, and conceptual appeal. The uncertainty typically associated with clustering tasks is formulated in this approach by allowing the assignment of each training vector to multiple clusters in the early stages of the iterative codebook design process. A training vector assignment strategy is also proposed for the transition from the fuzzy mode, where each training vector can be assigned to multiple clusters, to the crisp mode, where each training vector can be assigned to only one cluster. Such a strategy reduces the dependence of the resulting codebook on the random initial codebook selection. The resulting algorithms are used in image compression based on vector quantization. This application provides the basis for evaluating the computational efficiency of the proposed algorithms and comparing the quality of the resulting codebook design with that provided by competing techniques. <s> BIB001 </s> Image Compression: A Survey <s> COMPRESSION BASED ON FUZZY ALGORITHMS <s> Quantisation prior to the integer wavelet transform (Pre-Qnt) is introduced. The best combination of the Pre-Qnt and the conventional post-quantisation (Post-Qnt) in multi-stage band splitting based on the integer wavelet transform is presented. <s> BIB002
Fuzzy vector quantization algorithms: An algorithms which perform efficiently and exploit advantage of fuzzy clustering is propose where demands of VQ problem is also fulfilled. Effective strategies are milestone on which it is based upon for transition from soft toward crisp/hard decisions during the clustering process. Measurement of the uncertainty related to training vector assignment is also done in this study with the help of several functions which contain which are implemented in fuzzy K-means algorithms. For designing codebook in compression of image based on VQ the proposed Algorithms can also used BIB001 . A new VQ technique is presented in study which uses FRLVQ before applying Standard VQ algorithm as a pre process. The proposed algorithm helps to design codebook in an image compression application. An improvement in resulting codebook PSNR is achieved by FRLVQ-fuzzy VQ is shown by the experimental results. In selection RL is insensitive indicated by further testing both the learning rate control parameter and of the initial codebook BIB002 .