원문정보
초록
영어
As the digital information must be stored and recovered in an effective ways, it is necessary to compress data in image coding, wavelet transform and lattice vector quantization are adopted in this paper to improve the compression effective of image coding. We first propose the two dimensional spatial wavelet decomposition of image, and then we present lattice Vector Quantization coding scheme for each image subband, lattice vector quantization can make full use of the correlation between the image wavelet coefficients to remove the information redundancy, and the coding method of lattice quantization can be effective because of applying the symmetries of the lattice. The establishment of rate distortion (RD) model suitable for lattice vector quantization of wavelet image coder is also important for image compression, study shows that the RD performance for the spatial subbands are fitted by an exponential form theoretical model, this yields an analytical solution to the bit rate distribution issue, we explore an effective rate control scheme by using the lagrangian optimization method to distribute the bit rate for the spatial subbands. The experimental results show that the proposed algorithm can achieve better compressing effect with minimum loss.
목차
1. Introduction
2. Wavelet Decomposition of Image
3. Wavelet Based Image Coding using Lattice Vector Quantization
3.1. Wavelet Based Image Coding with Vector Quantization
3.2. Lattice Vector Quantization
3.3. Lattice Vector Quantization Codebook Design
4. RD Performance for Single Subband
4.1. Bit Rate Estimation for Single Subband
4.2. The Distortion Estimation for a Single Subband
4.3. RD Performance for a Single Subband
5. Rate Control for the Image Coder
5.1. The Description of Rate Control Problem
5.2. The Proposed Rate Control Algorithm
6. Experimental Results
7. Conclusions
Acknowledgements
References