A No-Reference Blur Metric based on Second-Order Gradients of Image

Estimation of the blurriness value in an image is an important issue in the image processing applications such as image deblurring. In this paper, a no-reference blur metric with a low computational cost is proposed, which is based on the difference between the second-order gradients of a sharp image and the one associated with its blurred version. The experiments, in this work, are performed on four databases including CSIQ, TID2008, IVC, and LIVE. The experimental results obtained indicate the capability of the proposed blur metric in measuring image blurriness and also the low computational cost compared with the other existing approaches.