Perceptual dissimilarity metric: A full reference objective image quality measure to quantify the degradation of perceptual image quality

This paper introduces a full reference objective image quality measure to quantify the degradation of perceptual image quality. Objective methods for assessing perceptual image quality are important for many image processing applications, such as monitoring and controlling image quality for quality control systems, benchmarking image processing systems and so on. The novel image quality metric proposed in this paper uses a relatively small number of pair-wise intensity comparisons to represent a patch as binary string, then compares corresponding patches using Hamming distances. It then calculates a dissimilarity value between images as an average of the Hamming distances computed between patches. The proposed metric is more consistent with human visual system and thus outperforms other existing and widely used metrics, namely the root mean square error (RMSE) and structural similarity index (SSIM). The computational cost of the proposed metric is also less compared to the state-of-the-art method.