A new approach of image quality index

Abstract

Image quality measurement procedures the quality of images automatically constructed on subjective evaluation. The smallest element of an image is pixel, can be converted to structure based evaluation using structure similarity index. We are proposed a novel modified feature similarity index (MFSIM) for image quality assessment (IQA) in this paper. This index used three features of an image namely Phase Congruency (PC), Gradient Magnitude (GM) and Angle (theta). The primary feature of MFSIM is PC which is contrast in variant system and measure the local structure of images. GM is the secondary feature which plays a complementary role. The angle of an image uses as tertiary feature of MFSIM. For this index need weighting function for evaluating of features and PC act as weighting function. All the task performs using five databases. The result of this proposed method shows higher rank-order correlation, low MSE than any other method like human visual system (HVS).