A Frequency Sensitivity-Based Quality Prediction Model for JPEG Images
A quality prediction model for images coded with JPEg is proposed in this paper. This model estimates the quality of an image at a given compressed ratio based on the structural similarity theory, without actual coding of the image. As different frequencies play various roles in human vision, the frequency sensitivity-based structural similarity model is introduced in this paper. The proposed model has a better correlation with the subjective judgment of human observers than both commonly used PSNR and newly proposed SSIM, because it emphasizes more on human eyes sensitive frequency bands. Experimental results with real images also show that the prediction error is less than 0.1 structural similarity index for over 80% test images.
David W. Tsai Yu-Jin Zhang
Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China Department of Electronic Engineering, Tsinghua University, Beijing 100084, 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
28-32
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）