Title :
Image compression using VQ and fuzzy classified algorithm
Author :
Tsay, Mu-King ; Jen-Fa Huang ; Chang-Chung, Wei-Ping
Author_Institution :
Dept. of Electr. Eng., Nat. Central Univ., Chung-Li, Taiwan
Abstract :
A fuzzy clustering algorithm is used for the image tree structure vector quantization (TSVQ). First, a digital image is divided into subblocks of fixed size, which consists of 4×4 blocks of pixels. By performing a 2-D discrete cosine transform (DCT), we select six DCT coefficients to form the feature vector, and use the fuzzy c-means algorithm in constructing the TSVQ codebook. By doing so, the algorithm can preserve the edge of image, make good image quality, and reduce the processing time while constructing the tree structured codebook, and reduce coding and decoding time
Keywords :
discrete cosine transforms; fuzzy set theory; image coding; vector quantisation; 2D discrete cosine transform; coding time; decoding time; digital image; feature vector; fuzzy c-means algorithm; fuzzy classified algorithm; fuzzy clustering algorithm; image compression; image quality; image tree structure vector quantization; tree structured codebook; Clustering algorithms; Degradation; Digital images; Discrete cosine transforms; Distortion measurement; Image coding; Image storage; Signal design; Tree data structures; Vector quantization;
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-3280-6
DOI :
10.1109/ICSMC.1996.569818
