The field of perceptual quality assessment has gone through a wide range of developments
and it is still growing. In particular, the area of no-reference (NR) image and video quality …

Visual quality evaluation has numerous uses in practice, and also plays a central role in
shaping many visual processing algorithms and systems, as well as their implementation …

In this paper, we propose a new no-reference (NR)/blind sharpness metric in the
autoregressive (AR) parameter space. Our model is established via the analysis of AR …

Blur is a key determinant in the perception of image quality. Generally, blur causes spread of
edges, which leads to shape changes in images. Discrete orthogonal moments have been …

Accurate estimation of Gaussian noise level is of fundamental interest in a wide variety of
vision and image processing applications as it is critical to the processing techniques that …

Recent advances in sparse representation show that overcomplete dictionaries learned from
natural images can capture high-level features for image analysis. Since atoms in the …

Universal blind image quality assessment (IQA) metrics that can work for various distortions
are of great importance for image processing systems, because neither ground truths are …

Abstract Evaluation of noise content or distortions present in an image is same as assessing
the quality of an image. Measurement of such quality index is challenging in the absence of …

No-reference measurement of perceptual image quality is a crucial and challenging issue in
modern image processing applications. One of the major difficulties is that some inherent …

Recently, some global contrast-based salient region detection models have been proposed
based on only the low-level feature of color. It is necessary to consider both color and …