Title :
A Flexible Non-linear PCA Encoder for Still Image Compression
Author :
Lv, Chuanfeng ; Liu, ZhiWen ; Zhao, Qiangfu
Author_Institution :
Beijing Inst. of Technol., Beijing
Abstract :
The main hindrance to develop a principal component analysis (PCA) encoder for image compression is the poor generalization ability of PCA. In this paper, we present a flexible semi-universal image encoder based on the recently proposed non-linear PCA framework. Unlike other PCA techniques with a fixed order of principal components, the proposed encoder can flexibly determine which component is more significant to the quality of compression according to the characteristics of the sub-image block to encode. The proposed encoder is used to compress still gray level images, and experimental results indicate that it can provide very good generalization ability as well as high compression ratio.
Keywords :
data compression; image coding; principal component analysis; compression quality; compression ratio; flexible nonlinear PCA encoder; flexible semiuniversal image encoder; principal component analysis encoder; still image compression; subimage block characteristics; Covariance matrix; Decoding; Discrete cosine transforms; Discrete transforms; Image coding; Information science; Information systems; Information technology; Principal component analysis; Training data;
Conference_Titel :
Computer and Information Technology, 2007. CIT 2007. 7th IEEE International Conference on
Conference_Location :
Aizu-Wakamatsu, Fukushima
Print_ISBN :
978-0-7695-2983-7
DOI :
10.1109/CIT.2007.164