Title of article :
FAST IMAGE COMPRESSION ALGORITHMS BASED ON VECTOR QUANTIZATION
Author/Authors :
swilem, a. minia university - faculty of science - computer science dept, Egypt
Abstract :
Vector quantization (VQ) is a well-known compression method In the encoding phase, given a block represented as a vector, searching the closest codeword in the codebook is a timeconsuming task In this paper, two fast encoding algorithms for VQ are proposed To reduce the search area and accelerate the search process, the first algorithm utilizes three significant features of a vector that are, the norm, and two projection angles to two projection axes. The second algorithm uses the first two features as in the first algorithm with the projection value of the vector to the second projection axe. The algorithms allow significant acceleration in the encoding process. Experimental results are presented on image block data. These results confirm the effectiveness of the proposed algorithms.
Keywords :
Annular and Angular constraints , EENNS algorithm , Projection axe , Vector quantization
Journal title :
International Journal of Intelligent Computing and Information Sciences
Journal title :
International Journal of Intelligent Computing and Information Sciences