Entropy Improvement for Fractal Image Coder

Entropy Improvement for Fractal Image Coder

Jyh-Horng Jeng, Shuo-Li Hsu, and Yukon Chang
 Department of Information Engineering, I-Shou University, Taiwan
 
Abstract: Fractal Image Coder (FIC) makes use of the self-similarity inside a natural image to achieve high compression ratio and maintain good image quality. In FIC, the most important factor affecting the compression ratio and the image quality is the quantization of the contrast scaling and brightness offset coefficients. Most quantization methods treat the two coefficients independently and quantize them separately. However, the two coefficients are highly correlated and scatter around a line. In this paper, a joint coefficient quantization method is proposed that considers the two coefficients together and thereby achieves better compression ratio and image quality. The proposed method is especially effective under parsimonious conditions. For example, using only 3 bits each to represent the contrast and brightness coefficients of Lena, the proposed method yields quality of 27.04 dB, which is significantly better than 22.87 dB obtained from the traditional linear quantization msethod.

Keywords: Fractal image coder, dihedral transformation, entropy, quantization, contrast adjustment, and brightness offset.


Received March 09, 2010; accepted October 24, 2010

Read 3598 times Last modified on Tuesday, 15 November 2011 07:34
Share
Top
We use cookies to improve our website. By continuing to use this website, you are giving consent to cookies being used. More details…