Quality Constrained Compression Using DWT-Based Image Quality Metric

A quality constrained compression algorithm based on Discrete Wavelet Transform (DWT) is proposed. The spatial-frequency decomposition property of DWT provides possibility for not only the new compression algorithm, but also a frequency-domain quality assessment method that can be executed in real-time. For this propose, a new quality metric in the wavelet domain called WNMSE is suggested, which assesses the quality of an image with the weighted sum of normalized mean square errors of the wavelet coefficients. The metric is consistent with the human judgment of visual quality as well as estimates the post-compression quality of an image efficiently. Based on the relationship among the statistic features, quantization step-sizes, and WNMSE value of a compressed image, we develop a Quality Constrained Quantization algorithm which can determine the quantization step-sizes for all the wavelet subbands for compressing the image to a desired visual quality accurately.

• Type: Journal
• Year: 2008
• Where: TCSV
• Authors: Zhigang Gao, Yuan F. Zheng
• Keywords: Discrete Wavelet Transform, Quality Constrained Compression, TCSV 2008, Wavelet