Color image quality assessment based on gradient similarity and distance transform

Abstract

In this paper, a new full-reference image quality assessment (IQA) metric is proposed. It is based on a Distance transform (DT) and a gradient similarity. The gradient images are sensitive to image distortions. Consequently, investigations have been carried out using the global variation of the gradient and the image skeleton for computing an overall image quality prediction. First, color image is transformed to YIQ space. Secondly, the gradient images and DT are identified from Y component. Thirdly, color distortion is computed from I and Q components. Then, the maximum DT similarity of the reference and test images is defined. Finally, combining the previous metrics the difference between test and references images is derived. The obtained results have shown the efficiency of the suggested measure.