Image compression using VQ and fuzzy classified algorithm

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/spl times/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.

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