Rate-distortion optimization of the image compression algorithm based on the warped discrete cosine transform

Authors:
Il Koo Kim;Nam Ik Cho;Sanjit K. Mitra
Affiliations:
School of Electrical Engineering and INMC, Seoul National University, Shilim-Dong, Kwanak-Ku, Seoul 151-744, South Korea;School of Electrical Engineering and INMC, Seoul National University, Shilim-Dong, Kwanak-Ku, Seoul 151-744, South Korea;Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA
Venue:
Signal Processing
Year:
2003

Citing 7
Cited 0

Numerical recipes in C (2nd ed.): the art of scientific computing

Numerical recipes in C (2nd ed.): the art of scientific computing
Data structures and algorithm analysis in C++

Data structures and algorithm analysis in C++
Digital Signal Processing: A Computer-Based Approach

Digital Signal Processing: A Computer-Based Approach
JPEG Still Image Data Compression Standard

JPEG Still Image Data Compression Standard
Adaptive Laguerre-lattice filters

IEEE Transactions on Signal Processing
Joint thresholding and quantizer selection for transform image coding: entropy-constrained analysis and applications to baseline JPEG

IEEE Transactions on Image Processing
Warped discrete cosine transform and its application in image compression

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.08

Visualization

Abstract

Recently, an image compression algorithm based on the warped discrete cosine transform has been proposed (Cho and Mitra, IEEE Trans Circuits Systems Video Technol 10 (8) (2000) 1364). The algorithm outperforms JPEG, especially for images with high frequency contents and compound images consisting of picture and text. In this paper, we improve the compression performance by optimizing the parameters of WDCT in the rate-distortion (R-D) sense, whereas the algorithm of Cho and Mitra considers distortion only. The optimization algorithm finds the WDCT matrices for each block which minimize the distortion for the given bit budget. The problem is formulated in a form that can be solved by the Lagrange multiplier technique. The major difference of the proposed algorithm from the conventional optimized JPEG is that the proposed algorithm controls the rate and distortion by warping the frequency contents of input signals before DCT, whereas the conventional optimized JPEG controls the R-D by manipulating the data after DCT, i.e. by adjusting the quantization matrix. The simulation results show that the proposed algorithm yields better performance than the conventional optimized JPEG at high bit rates and for images with high frequency components. Moreover, the proposed algorithm requires lower computational complexity, because only a single parameter is controlled to meet the R-D constraints.