Artifact reduction of JPEG coded images using mean-removed classified vector quantization

A fast search algorithm for mean-removed vector quantization using edge and texture strengths of a vector

“…For example, the execution time of the algorithm presented in Ref. [5], can be effectively reduced by applying the proposed fast search algorithm. It is noted that our algorithm and the full search method have the same image quality.…”

“…With its relatively simple structure and computation, VQ has received great attention in the last decade [1][2][3][4][5][6][7][8][9][10][11]. Many types of VQ, such as classified VQ [1], address VQ [2], finite state VQ [3], side match VQ [4], mean-removed classified VQ [5], and predictive classified VQ [6], have been used for various purposes. VQ has been applied to some other applications, such as index compression [7], and inverse halftoning [8,9].…”

Multilevel Compression Scheme using Vector Quantization for Image Compression

“…If the value is > t2 and <= t3, it is coded as 10 other wise 11. Now the coded bitplane for any codevector will be like [11,11,01, 00, 11, 11, 01, 00, 11, 10, 10, 00, 11, 10, 01, 00] and the codevector is replaced with the set of coded bit plane, a and d. Generally, a codeword takes 16 x 8 = 128 bits. But after compression using 4- …”

"Performance Comparison of LBG, KPE, KFCG and KMCG for Global Codebook Technique"

“…The response time is very important factor for real time application [1]. M any type of VQ, such as classified VQ [9], [10], address VQ [9], [11], finite state VQ [9], [12], side match VQ [9], [13], mean-removed classified VQ [9], [14], and predictive classified VQ [9], [15], have been used for various purposes Vector Quantization (VQ) is a compression technique based on grouping blocks of information based on the similarity of their values. There is a loss of quality while using VQ, but this is duly compensated by the significant savings achieved by this compression method.…”