Quad-tree partitioned fractal coding based on region competition strategy

Yonghong Chen; Zelin Shi

doi:10.1117/12.747843

14 November 2007 Quad-tree partitioned fractal coding based on region competition strategy

Yonghong Chen, Zelin Shi

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679040 (2007) https://doi.org/10.1117/12.747843
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

To deal with the time-consuming problem in the fractal coding, a novel method based on the region competition strategy is introduced to improve the speed of fractal coding effectively. This strategy adopted can discover the optimal affine matching block and the optimal affine transformation of each range block, improving some affine ones with bigger error. Experiments on still life image, fractal image and remote sensing image show that the proposed scheme reduces the compression time and obtains the approximate reconstruction fidelity while it has the same compression ratios as that of adaptive quad-tree partitioned fractal coding.

Citation Download Citation

Yonghong Chen and Zelin Shi "Quad-tree partitioned fractal coding based on region competition strategy", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679040 (14 November 2007); https://doi.org/10.1117/12.747843

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available