In this paper, we present an extensive review on deep learning methods for image
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …

The important criteria used in subjective evaluation of distorted images include the amount
of distortion, the type of distortion, and the distribution of error. An ideal image quality …

The wide variety of distortions that images are subject to during acquisition, processing,
storage, and reproduction can degrade their perceived quality. Since subjective evaluation …

Perceptual approaches have been widely used in many areas of visual information
processing. This paper presents an overview of perceptual based approaches for image …

As the essential content of intelligent animal husbandry, identifying each livestock is the only
way to achieve modern and refined scientific husbandry. This paper proposes a sheep face …

In this paper, we propose a neural network approach to image quality assessment. In
particular, the neural network measures the quality of an image by predicting the mean …

This paper aims to give a survey of full-reference image quality metrics, including metrics
specifically designed to evaluate image quality, but also metrics for image difference, image …

The objective assessment of image quality is an essential part of many visual processing
systems. The challenge lies in evaluating the image quality consistently under subjective …

Image quality assessment is an important component in every image processing system
where the last link of the chain is the human observer. This domain is of increasing interest …

This paper demonstrates the usefulness of spatial/spatial-frequency representations in
image quality assessment by introducing a new image dissimilarity measure based on 2D …