Reduced Reference Image Quality Assessment Based on Contourlet Domain and Natural Image Statistics
Reduced-reference (RR) image quality assessment metrics (IQA) evaluate the quality of images by extracting a parameter set from the original reference image and using this set in place of the actual reference image. In this paper, we propose a novel RR-IQA metric based on Contourlet transform. By combining Contourlet transform with a version of the hidden Markov model-Gaussian scale mixtures (GSM), the marginal distributions of neighbor coefficients in the Contourlet domain are modeled. With Contourlet transform as a pre-processing, the marginal histograM of coefficients in each subband can be well fitted by Guassian distribution after divisive normalization transforming. The standard derivation of the fitted Guassian transform and fitted error will be extracted as feature parameters. Experiments show that the proposed metric has good consistency with human subjective perception.
Xu Wang Gangyi Jiang Mei Yu
Faculty of Information Science and Engineering, Ningbo University Ningbo University, Ningbo, China
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
45-50
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）