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MUNIQUE: Multiview no-reference image quality evaluation

This paper presents a novel no-reference objective algorithm for stereoscopic image quality assessment, called MUNIQUE, which is based on the estimation of both two-dimensional and stereoscopic features of images, namely local estimations of blockiness and blurriness and the disparity weighting technique. Applications of stereoscopic image and video quality assessment in surveillance systems are discussed. Simulation results using LIVE 3D Image Quality Database Phase I, which includes Gaussian blur and fast fading degraded images, are presented and a comparison of performance of MUNIQUE with several state of the art algorithms is made. Correlation coefficients between subjective and predicted scores indicate a superior performance of the proposed algorithm, when it is compared with others no-reference algorithms. An implementation of the proposed algorithm coded in C# programming language is publicly available at: https://sites.google.com/site/jvmircas/home/munique.