A no-reference sharpness metric based on the notion of relative blur for Gaussian blurred image

• The notion of relative blur that corresponds well with HVS perception is proposed.
• A granularity analysis is put forward for determining the scale fineness.
• Modifications are introduced to a traditional edge width metric for robustness.

This work presents a no-reference sharpness metric for Gaussian blurred image. The metric is based on the notion of relative blur. The key concept is that the judgement on the sharpness closely relates to the degree of convenience for recognizing image objects on a certain scale. Based on this concept, the proposed metric is defined as relative blur with respect to certain object scale using an absolute blur measure. The object scale is characterized by a granularity analysis of image content. And the absolute blur is built on an analysis of edge local gray level distribution. The performance of the metric is tested and compared with some outstanding existing metrics in this field on three widely used databases. The experiment results show that the proposed metric can predict the sharpness of images in varying databases with high accuracy and reliability.