An Image Quality Assessment Technique using Defocused Blur as Evaluation Metric

In this paper, an image quality assessment technique based on defocus blur identification is proposed. Some representative image regions containing edge features are first extracted automatically. A histogram analysis based on the comparison of real and synthesized defocused regions is then carried out to estimate the blur extent. By iteratively changing the convolution parameters, the best blur extent is identified from histogram matching. The image quality is finally evaluated based on the overall blur extent of the selected regions. We have performed the experiments using real scene images. It is shown that accurate image quality assessment results can be achieved using the proposed technique.