No-Reference Quality Assessment of the Gaussian Blur Image Depending on Local Standard Deviation

Abstract

No-reference measurement of blurring artifacts in images isa difficult problem in image quality assessment field. In this paper, we present a no-reference blur metric to estimatethe quality of theimages. These images are degraded using Gaussian blurring. Suggestion method depends on developing the Mean of Locally Standard deviation this method is called Blur Quality Metric (BQM) and itcalculatesby using gamma correction and reblurring the image again And the BQM is compared with the No-reference Perceptual Blur Metrics (PBM)and the Entropy of the First Derivative (EFD) Image; the BQM is a simple metric and gives good accuracy in metrics the quality for theGaussian blurred image if it compared with another algorithms. The BQM satisfied high correlation coffecion compared with another method.

Keywords: No-referencequality assessment, Gaussian blurring, Standard deviation, mean.