Abstract

With the growing demand for image and video-based applications, the requirements of consistent quality assessment metrics of image and video have increased. Different approaches have been proposed in the literature to estimate the perceptual quality of images and videos. These approaches can be divided into three main categories; full reference (FR), reduced reference (RR) and no-reference (NR). In RR methods, instead of providing the original image or video as a reference, we need to provide certain features (i.e., texture, edges, etc.) of the original image or video for quality assessment. During the last decade, RR-based quality assessment has been a popular research area for a variety of applications such as social media, online games, and video streaming. In this paper, we present review and classification of the latest research work on RR-based image and video quality assessment. We have also summarized different databases used in the field of 2D and 3D image and video quality assessment. This paper would be helpful for specialists and researchers to stay well-informed about recent progress of RR-based image and video quality assessment. The review and classification presented in this paper will also be useful to gain understanding of multimedia quality assessment and state-of-the-art approaches used for the analysis. In addition, it will help the reader select appropriate quality assessment methods and parameters for their respective applications.

Highlights

  • The demand for image and video quality assessment is growing rapidly in the emerging multimedia applications

  • Point-based techniques are mostly used for 2D-image quality estimations and the values used in the performance are based on the amount of how much the image is distorted by compression technique

  • The Natural Image Statistic Metric (NISM) method has been documented as the normal approach for RR multimedia contents quality, it fails to deliberate the statistical associations of wavelet coefficients in dissimilar subbands and the visual reaction characteristics of the mammalian cortical simple cells [107]

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Summary

Introduction

The demand for image and video quality assessment is growing rapidly in the emerging multimedia applications. Our contribution presents an overview of RR quality assessment metrics with respect to domain-based classification (i.e., pixel, frequency, and bitstream) that helps in selection of the metrics according to the required multimedia contents (i.e., image, videos, 2D or 3D based). Fast Johnson–Lindenstrauss transform (FJLT)-based image hashing technique for RR approach provides the low data-rate features of multimedia content for reference and accurately estimates the quality degraded by JPEG and JPEG2000 compression [66].

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