No-Reference Image Quality Assessment Using Euclidean Distance Matrices

Image quality assessment (IQA) methods play important roles in many applications such as image communication, reception, compression, restoration, and display. No-reference IQA metrics are required to resolve an image when there is a lack of a reference image that is required for fullreference IQA metrics. We propose a no-reference IQA method to evaluate the image quality by using the difference between the distribution width of the recorded block pixel correlative matrix (PCM) and the distribution width of the recorded block Euclidean distance matrix (EDM) of the PCM (EDM– PCM). Euclidean distance is generally used to measure the similarity between two pixels, and an image EDM is built by calculating the Euclidean distance between two same-size image blocks centered on two different pixels. Images with different noise have different PCM distribution widths, and the original image has a wider PCM distribution width as well as a noised image with narrower PCM distribution width. The calculated EDM–PCMs suggest that noised images have a narrower EDM–PCM distribution width. Therefore, the distribution widths of the EDM–PCM and the image PCM can be used as an image quality assessment index. The assessment results suggest that the proposed method is effective in evaluating the quality of images with Gaussian blur, global contrast decrements, and JPEG2000 compressed noise.