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Krishnamoorthy, R.
- Low Complexity Hybrid Lossy to Lossless Image Coder with Combined Orthogonal Polynomials Transform and Integer Wavelet Transform
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1 Department of Computer Science and Engineering, Anna University of Technology, Tiruchirappalli, IN
1 Department of Computer Science and Engineering, Anna University of Technology, Tiruchirappalli, IN
Source
ICTACT Journal on Image and Video Processing, Vol 2, No 4 (2012), Pagination: 410-416Abstract
In this paper, a new lossy to lossless image coding scheme combined with Orthogonal Polynomials Transform and Integer Wavelet Transform is proposed. The Lifting Scheme based Integer Wavelet Transform (LS-IWT) is first applied on the image in order to reduce the blocking artifact and memory demand. The Embedded Zero tree Wavelet (EZW) subband coding algorithm is used in this proposed work for progressive image coding which achieves efficient bit rate reduction. The computational complexity of lower subband coding of EZW algorithm is reduced in this proposed work with a new integer based Orthogonal Polynomials transform coding. The normalization and mapping are done on the subband of the image for exploiting the subjective redundancy and the zero tree structure is obtained for EZW coding and so the computation complexity is greatly reduced in this proposed work. The experimental results of the proposed technique also show that the efficient bit rate reduction is achieved for both lossy and lossless compression when compared with existing techniques.Keywords
Orthogonal Polynomials Transform Coding, Integer Wavelet Transform, Embedded Zerotree Coding.- Autoregressive Model Based on Bayesian Approach for Texture Representation
Abstract Views :174 |
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Authors
Affiliations
1 Department of Computer Science, PSG College of Arts and Science, IN
2 Department of Computer Science and Engineering, Anna University, Tiruchirappalli, IN
1 Department of Computer Science, PSG College of Arts and Science, IN
2 Department of Computer Science and Engineering, Anna University, Tiruchirappalli, IN