Paper
30 May 2000 Improved fractal image coding using subblock luminance shifting
Author Affiliations +
Proceedings Volume 4067, Visual Communications and Image Processing 2000; (2000) https://doi.org/10.1117/12.386668
Event: Visual Communications and Image Processing 2000, 2000, Perth, Australia
Abstract
This paper presents an improved fractal block coding scheme for still images. The proposed scheme employs a new technique which we call `sub-block luminance level shifting.' In fractal block coding, an input image is first partitioned into range blocks. Each range block is encoded by a set of contractive affine transformations of its corresponding domain block. One of the coded data for each range block is an average pixel value of the range block, which is used for luminance level shifting between the range block and the contracted domain block. In our proposed method, a range block is further partitioned into sub-blocks in some cases and an average value of each sub-block instead of the range block is used for luminance level shifting. We have proposed an improved fractal block coding scheme applying this sub-block luminance level shifting adaptively block-by-block basis and also combining this method with adaptive range block size fractal coding. The computer simulation results show that the proposed fractal coding scheme gives higher SNR (Signal-to- Noise Ratio) values and better image qualities compared to the conventional fractal block coding scheme.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Katsutoshi Sawada, Yuuki Hiraiwa, and Eiji Nakamura "Improved fractal image coding using subblock luminance shifting", Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); https://doi.org/10.1117/12.386668
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Fractal analysis

Image compression

Signal to noise ratio

Computer programming

Image quality

Distortion

Computer simulations

RELATED CONTENT


Back to Top