▪ Abstract It has long been assumed that sensory neurons are adapted, through both
evolutionary and developmental processes, to the statistical properties of the signals to …

Attention has been found to have a wide variety of effects on the responses of neurons in
visual cortex. We describe a model of attention that exhibits each of these different forms of …

We propose a referenceless perceptual fog density prediction model based on natural
scene statistics (NSS) and fog aware statistical features. The proposed model, called Fog …

We propose a natural scene statistic-based distortion-generic blind/no-reference (NR)
image quality assessment (IQA) model that operates in the spatial domain. The new model …

Blind image quality assessment (BIQA) aims to evaluate the perceptual quality of a distorted
image without information regarding its reference image. Existing BIQA models usually …

Our approach to blind image quality assessment (IQA) is based on the hypothesis that
natural scenes possess certain statistical properties which are altered in the presence of …

Current top-performing blind perceptual image quality prediction models are generally
trained on legacy databases of human quality opinion scores on synthetically distorted …

Objective methods for assessing perceptual image quality traditionally attempted to quantify
the visibility of errors (differences) between a distorted image and a reference image using a …

We propose a definition of saliency by considering what the visual system is trying to
optimize when directing attention. The resulting model is a Bayesian framework from which …

This Lecture book is about objective image quality assessment—where the aim is to provide
computational models that can automatically predict perceptual image quality. The early …