A Novel No-Reference Perceptual Blur Metric

Abstract

In this paper, we present a novel no-reference blur metric for images. The blur metric is based on analyzing image features include the mean value of phase congruency image, the entropy of phase congruency image and the distorted image, and the gradient of the distorted image. The new index does NOT need any information from reference image, and image quality estimation is accomplished by simple functional relationship between those features. Our experimental results show that the new index outperforms existing popular no-reference blurriness metric and full reference PSNR on LIVE Gaussian blurred database and IVC blurring images.