Image quality assessment (IQA) continues to garner great interest in the research community, particularly given the tremendous rise in consumer video capture and streaming. Despite significant research effort in IQA in the past few decades, the area of noreference image quality assessment remains a great challenge and is largely unsolved. In this paper, we propose a novel no-reference image qua...

When an image is supposed to have been transformed by a process like image enhancement or lossy image compression for storing or transmission, it is often necessary to measure the quality of the distorted image. This can be achieved using an image processing method called “quality criterion”. Such a process must produce objective quality scores in close relationship with subjective quality scor...

The goal of image or video quality assessment is to evaluate if a distorted image or video is of a good quality by measuring the difference between the original and distorted images or videos. In this paper, to assess the visual quality of an arbitrary distorted image or a compressed video, visual features of the image or video are compared with those of the original image or video instead of d...

In this paper, a novel reduced-reference (RR) image quality assessment (IQA) is proposed by depicting the intraand inter-subband statistical characteristics in the reorganized discrete cosine transform (DCT) domain. Firstly, the block-based DCT coefficients are reorganized into a threelevel tree. Generalized Gaussian density (GGD) function is employed to capture the intra-subband characteristic...

Recently, research of Objective Image Quality Assessment (IQA) has gained much attention due to its wide application prospect. Among them, the Reduced-Reference (RR) methods estimate perceptual quality of distorted images with partial information from the reference images. This paper proposes a novel universal RR-IQA metric based on the statistics of edge patterns. Firstly, the binary edge maps...

Providing a satisfactory visual experience is one of the main goals for present-day electronic multimedia devices. All the enabling technologies for storage, transmission, compression, rendering should preserve, and possibly enhance, the quality of the video signal; to do so, quality control mechanisms are required. These mechanisms rely on systems that can assess the visual quality of the inco...

Image quality assessment (IQA) is in great demand for high quality image selection in the big data era. The challenge of reduced-reference (RR) IQA is how to use limited data to effectively represent the visual content of an image in the context of IQA. Research on neuroscience indicates that the human visual system (HVS) exhibits obvious orientation selectivity (OS) mechanism for visual conten...

This chapter is about objective image quality assessment (IQA), which has been recognized as an effective and efficient way to predict the visual quality of distorted images. Basically, IQA has three different dependent degrees on original images, namely, full-reference (FR), noreference (NR), and reduced-reference (RR). To begin with, the fundamentals of IQA are introduced and a broad treatmen...

This paper studies the problem of full reference visual quality assessment of denoised images with a special emphasis on images with low contrast and noise-like texture. Denoising of such images together with noise removal often results in image details loss or smoothing. A new test image database, FLT, containing 75 noise-free ‘reference’ images and 300 filtered (‘distorted’) images is develop...

Measuring visual quality, as perceived by human observers, is becoming increasingly important in a large number of applications where humans are the ultimate consumers of visual information. Many natural image databases have been developed that contain human subjective ratings of the images. Subjective quality evaluation data is less available for synthetic images, such as those commonly encoun...