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Reduced reference image and video quality assessments: review of methods
TIB, Leibniz Information Centre for Science and Technology, DEU.ORCID iD: 0000-0001-5712-1565
National University of Computer and Emerging Sciences, PAK.
National University of Computer and Emerging Sciences, PAK.
National University of Computer and Emerging Sciences, PAK.
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2022 (English)In: EURASIP Journal on Image and Video Processing, ISSN 1687-5176, E-ISSN 1687-5281, Vol. 2022, no 1, article id 1Article, review/survey (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer, 2022. Vol. 2022, no 1, article id 1
Keywords [en]
Multimedia quality assessment, Reduced reference image quality approaches, Image quality parameters, Reduced reference video quality approaches, Video quality parameters
National Category
Signal Processing
Research subject
Applied Signal Processing
Identifiers
URN: urn:nbn:se:bth-22555DOI: 10.1186/s13640-021-00578-yISI: 000742003800001Scopus ID: 2-s2.0-85122961118OAI: oai:DiVA.org:bth-22555DiVA, id: diva2:1627560
Note

open access

Available from: 2022-01-13 Created: 2022-01-13 Last updated: 2022-01-31Bibliographically approved

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Reduced_reference_image_video_QA(3293 kB)112 downloads
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Shahid, MuhammadLövström, Benny

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