Image Quality Assessment based on Perceptual Blur Metric

The recent development of digital image acquisition technologies leads to better image quality, in terms of spatial resolution and sensitivity. Image quality is a characteristic of an image that measures the perceived image degradation. Several techniques and metrics are proposed which can be classified as Full-Reference (FR) method, No-Reference (NR) method and Reduced Reference (RR) method. In this field of image quality assessment, it is crucial to deep research the physiology and psychology of human visual system. However, it is obvious that strong correlation between the results and human visual perception is essential. In this paper, we propose a new approach for image quality assessment that combines the perceptual blur metric and the index of Structural Similarity (SSIM) in order to improve the image quality quantification.