Blind image quality assessment considering blur, noise, and JPEG compression distortions
Erez Cohen, Yitzhak Yitzhaky · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
The quality of images may be severely degraded in various situations such as imaging during motion, sensing through a diffusive medium, high compression rate and low signal to noise. Often in such cases, the ideal un-degraded image is not available (no reference exists). This paper overviews past methods that dealt with no-reference (NR) image quality assessment, and then proposes a new NR method for the identification of image distortions and quantification of their impacts on image quality. The proposed method considers both noise and blur distortion types that individually or simultaneously exist in the image. Distortion impacts on image quality are evaluated in the spatial frequency domain, while noise power is further estimated in the spatial domain. Specific distortions addressed here include additive white noise, Gaussian blur, de-focus blur, and JPEG compression. Estimation results are compared to the true distortion quantities, over a set of 75 different images.