A New Near-Lossless Image Compression Algorithm

Author

Xiaoqin, Wu ; Yaohong, Kang ; Hongke, Zhang ; Jiaxian, Deng

Author_Institution

Beijing Jiaotong Univ., Beijing

fYear

2007

fDate

23-25 May 2007

Firstpage

2813

Lastpage

2815

Abstract

This paper proposes a new near-lossless image compression algorithm, namely empirical data decomposition (EDD), which can carry on adaptive analysis to the observation data. The algorithm suits to analyze non-stationary data and can effectively remove the relevance between of observation data. In EDD, analysis filter is automatically determined by observation data, and is able to realize the multi-resolution analysis. Performing compression on continuous tone image and hyper-spectrum images with the improved EBCOT based on EDD and JPEG2000, respectively, the simulation results indicate that, in the case of high or higher code rate, EDD can obtain higher image compression efficiency.

Keywords

data compression; filtering theory; image coding; image resolution; JPEG2000; analysis filter; continuous tone image; empirical data decomposition; hyper-spectrum images; multiresolution analysis; near-lossless image compression algorithm; Algorithm design and analysis; Data analysis; Educational institutions; Fourier transforms; Image analysis; Image coding; Information science; Paper technology; Poles and zeros; Polynomials;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4244-0737-8

Electronic_ISBN

978-1-4244-0737-8

Type

conf

DOI

10.1109/ICIEA.2007.4318924

Filename

4318924