Research Member
Research Department
Research Year
2004
Research Journal
Proc. 4th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2004), Rome, Italy
Research Rank
3
Research_Pages
pp. 287-290
Research Abstract
Image compression using vector quantization (VQ) results in highly correlated indices. The correlation between these indices is used to reduce the bits needed to represent them. This is done by many index compression algorithms such as the Hu and Chang, search order coding (SOC), and switching tree coding (STC). A new algorithm for VQ index compression is introduced and it utilizes the local statistics of each image and the repeating pattern of its adjacent indices. The proposed algorithm improves the index compression performance of the basic VQ, with a relatively slight increase of complexity.