Title :
A multiple description coding method based on set partitioning in hierarchical trees algorithm for color images
Author :
Huang, Chin-Pan ; Hwang, Bor-Jiunn ; Mao, Chia-i ; Wang, Wei-chuan
Author_Institution :
Dept. of Comput. & Commun. Eng., Ming Chuan Univ., Taoyuan, Taiwan
Abstract :
In this paper, a new multiple description coding (MDC) method for color images is presented. The proposed approach bases on the set partitioning in hierarchical trees (SPIHT) algorithm to achieve a high image compression ratio; employs poly-phase sampling technique to generate multiple descriptions to adapt to varying Internet environments. It results in having capabilities to conquer packet losses and remaining the reconstructed images with an acceptable quality. In order to preserve the progressive reconstruction properties for a color image transmission, the three components (Red, Green, and Blue) are encoded separately and their encoding results are interleaved for transmission. The proposed method is applicable to color images and is very flexible for practical applications. The experimental results are given to illustrate the characteristics and verify the efficiency of the proposed method.
Keywords :
data compression; image coding; image colour analysis; image reconstruction; image sampling; trees (mathematics); SPIHT; acceptable quality; color image; hierarchical trees algorithm; image compression; image reconstruction; multiple description coding method; polyphase sampling technique; set partitioning; Color; Cybernetics; Image coding; Image reconstruction; Image sampling; Machine learning; Machine learning algorithms; Packaging; Partitioning algorithms; Wavelet transforms; MDC; Poly-phase Sampling; SPIHT; Wavelet transform;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212626