This paper focuses on an entropy based formalism to speed up the evaluation of the Structural SIMilarity (SSIM) index in images affected by a global distortion. Looking at images as information sources, a visual distortion typical set can be defined for SSIM. This typical set consists of just a subset of information belonging to the original image and the corresponding one in the distorted version. As side effect, some general theoretical criteria for the computation of any full reference quality assessment measure can be given in order to maximize its computational efficiency. Experimental results on various test images show that the proposed approach allows to estimate SSIM with a considerable speed up (about 200 times) and a small relative error (often lower than 5%).
An entropy based approach for SSIM speed up
Bruni V;Vitulano D
2017
Abstract
This paper focuses on an entropy based formalism to speed up the evaluation of the Structural SIMilarity (SSIM) index in images affected by a global distortion. Looking at images as information sources, a visual distortion typical set can be defined for SSIM. This typical set consists of just a subset of information belonging to the original image and the corresponding one in the distorted version. As side effect, some general theoretical criteria for the computation of any full reference quality assessment measure can be given in order to maximize its computational efficiency. Experimental results on various test images show that the proposed approach allows to estimate SSIM with a considerable speed up (about 200 times) and a small relative error (often lower than 5%).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
