A Hierarchical Classification Matching Scheme for Fractal Image Compression
- Resource Type
- Conference
- Authors
- Xing, Cangju; Ren, Yuan; Li, Xuebin
- Source
- 2008 Congress on Image and Signal Processing Image and Signal Processing, 2008. CISP '08. Congress on. 1:283-286 May, 2008
- Subject
- Signal Processing and Analysis
Computing and Processing
Fractals
Image coding
Image reconstruction
PSNR
Boats
Testing
Lattices
Signal processing
Chemical technology
Partitioning algorithms
- Language
A hierarchical classification matching scheme for fractal image compression is proposed in this paper. This scheme reduces the encoding time dramatically by partitioning the domain pools hierarchically. Experimental results on standard gray scale image show that the hierarchical classification matching scheme yields much better performance over other classification matching scheme. Compared with Fisher’s quadtree method, the encoding time of the proposed algorithm for Lena reduces by 84.07% in average, while the compression ratio increases by 14.56% and the PSNR of the reconstructed image is also increased by 3.23%.