No-reference image quality assessment needs no prior knowledge of reference image. A new fuzzy image quality measure (built from interval type-2 fuzzy sets (IFS2)) is compared with experimental psycho-visual data. The proposed measure is based on IFS2 entropy applied on synthetic images. A recently performed psycho-visual experiment provides psycho-visual scores on some synthetic images, and co...

We propose a universal no-reference (NR) image quality assessment (QA) index that does not require training on human opinion scores. The new index utilizes perceptually relevant image features extracted from the distorted image. These include the mean phase con-gruency (PC) of the image, the entropy of the phase congruencyPC image, the entropy of the distorted image, and the mean gradient magni...

Many dense 3D point clouds have been exploited to represent visual objects instead of traditional images or videos. To evaluate the perceptual quality various clouds, in this letter, we propose a novel and efficient Reduced-Reference metric for which is based on Content-oriented sAliency Projection (RR-CAP). Specifically, make first attempt simplify reference distorted into projected saliency m...