Real-time compression coding based on convolution fractal image

Fu Ping; Ke-bin An; Pei-zhen Zhang; Hexin Chen

doi:10.1117/12.477129

31 July 2002 Real-time compression coding based on convolution fractal image

Fu Ping, Ke-bin An, Pei-zhen Zhang, Hexin Chen

Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477129
Event: Second International Conference on Image and Graphics, 2002, Hefei, China

Abstract

In fractal image compression, an image is coded as a set of contractive transformations, and is guaranteed to generate an approximation to the original image when iteration applied to any initial image. In this paper, according to Jacquin' 5 PIFS algorithm, and by analyzing traditional fractal mapping parameters, a kind of convolution-based fast fractal image coding scheme (CBFC) is advanced. To speed up the encoding and improve the compression ratio, it is combined with quad-tree partitioning neighbor searching algorithm. To improve the real-time performance of the algorithm, it is performed on TMS320C6201. Experiments results of algorithms based on CBFC, and CBFC using quad-tree partitioning structure on DSP are given in this paper as comparisons. The results show that fractal image real-time coding can be realized with the considerable reconstructive image and coding time.

Citation Download Citation

Fu Ping, Ke-bin An, Pei-zhen Zhang, and Hexin Chen "Real-time compression coding based on convolution fractal image", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477129

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