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Quality Assessment of Stereoscopic 3D Image Compression by Binocular Integration Behaviors

Published: 01 April 2014 Publication History

Abstract

The objective approaches of 3D image quality assessment play a key role for the development of compression standards and various 3D multimedia applications. The quality assessment of 3D images faces more new challenges, such as asymmetric stereo compression, depth perception, and virtual view synthesis, than its 2D counterparts. In addition, the widely used 2D image quality metrics (e.g., PSNR and SSIM) cannot be directly applied to deal with these newly introduced challenges. This statement can be verified by the low correlation between the computed objective measures and the subjectively measured mean opinion scores (MOSs), when 3D images are the tested targets. In order to meet these newly introduced challenges, in this paper, besides traditional 2D image metrics, the binocular integration behaviors—the binocular combination and the binocular frequency integration, are utilized as the bases for measuring the quality of stereoscopic 3D images. The effectiveness of the proposed metrics is verified by conducting subjective evaluations on publicly available stereoscopic image databases. Experimental results show that significant consistency could be reached between the measured MOS and the proposed metrics, in which the correlation coefficient between them can go up to 0.88. Furthermore, we found that the proposed metrics can also address the quality assessment of the synthesized color-plus-depth 3D images well. Therefore, it is our belief that the binocular integration behaviors are important factors in the development of objective quality assessment for 3D images.

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  • (2024)Perceptual Depth Quality Assessment of Stereoscopic Omnidirectional ImagesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.344969634:12_Part_2(13452-13462)Online publication date: 1-Dec-2024
  • (2024)Objective Quality Assessment of Stereoscopic Video Using Inflated 3D FeaturesSN Computer Science10.1007/s42979-024-03184-75:6Online publication date: 15-Aug-2024
  • (2023)Information Visualization Based on Visual Transmission and Multimedia Data FusionInternational Journal of Information Technologies and Systems Approach10.4018/IJITSA.32022916:3(1-14)Online publication date: 22-Mar-2023
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  1. Quality Assessment of Stereoscopic 3D Image Compression by Binocular Integration Behaviors

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    cover image IEEE Transactions on Image Processing
    IEEE Transactions on Image Processing  Volume 23, Issue 4
    April 2014
    474 pages

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    IEEE Press

    Publication History

    Published: 01 April 2014

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    • (2024)Perceptual Depth Quality Assessment of Stereoscopic Omnidirectional ImagesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.344969634:12_Part_2(13452-13462)Online publication date: 1-Dec-2024
    • (2024)Objective Quality Assessment of Stereoscopic Video Using Inflated 3D FeaturesSN Computer Science10.1007/s42979-024-03184-75:6Online publication date: 15-Aug-2024
    • (2023)Information Visualization Based on Visual Transmission and Multimedia Data FusionInternational Journal of Information Technologies and Systems Approach10.4018/IJITSA.32022916:3(1-14)Online publication date: 22-Mar-2023
    • (2022)Reduced reference image and video quality assessments: review of methodsJournal on Image and Video Processing10.1186/s13640-021-00578-y2022:1Online publication date: 12-Jan-2022
    • (2022)Stereoscopic video quality measurement with fine-tuning 3D ResNetsMultimedia Tools and Applications10.1007/s11042-022-13485-981:29(42849-42869)Online publication date: 1-Dec-2022
    • (2022)A two-stream cnn based visual quality assessment method for light field imagesMultimedia Tools and Applications10.1007/s11042-022-13436-482:4(5743-5762)Online publication date: 30-Jul-2022
    • (2021)No-Reference Stereoscopic Image Quality Assessment Based on Binocular Statistical Features and Machine LearningComplexity10.1155/2021/88346522021Online publication date: 1-Jan-2021
    • (2021)A Layered Approach for Quality Assessment of DIBR-Synthesized ImagesWireless Communications & Mobile Computing10.1155/2021/83779362021Online publication date: 13-Nov-2021
    • (2021)Shape-Preserving Stereo Object Remapping via Object-Consistent Grid WarpingIEEE Transactions on Image Processing10.1109/TIP.2021.308994730(5889-5904)Online publication date: 1-Jan-2021
    • (2021)No-reference stereo image quality assessment based on discriminative sparse representationMultimedia Tools and Applications10.1007/s11042-021-11322-z80:21-23(33033-33053)Online publication date: 13-Aug-2021
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