04797nam 2200517 450 991061926760332120230305182155.0981-19-3347-2(MiAaPQ)EBC7119895(Au-PeEL)EBL7119895(CKB)25179632200041(PPN)265856558(EXLCZ)992517963220004120230305d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierQuality assessment of visual content /Ke Gu, Hongyan Liu and Chengxu ZhouSingapore :Springer,[2022]©20221 online resource (256 pages)Advances in computer vision and pattern recognitionPrint version: Gu, Ke Quality Assessment of Visual Content Singapore : Springer,c2022 9789811933462 Includes bibliographical references.Intro -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 Quality Assessment of Traditional Images -- 1.2 Quality Assessment of Screen Content Images -- 1.3 Quality Assessment of 3D-Synthesized Images -- 1.4 Quality Assessment of Sonar Images -- 1.5 Quality Assessment of Enhanced Images -- 1.6 Quality Assessment of Light-Field Images -- 1.7 Quality Assessment of Virtual Reality Images -- 1.8 Quality Assessment of Super-Resolution Images -- References -- 2 Quality Assessment of Screen Content Images -- 2.1 Introduction -- 2.2 Methodology -- 2.2.1 Full-Reference QA of Screen Content Images -- 2.2.2 Reduced-Reference QA of Screen Content Images -- 2.2.3 No-Reference QA of Screen Content Images -- 2.3 Comparison and Analysis of Algorithm Performance -- 2.3.1 Testing Database -- 2.3.2 Performance Comparison and Analysis -- 2.4 Conclusion -- References -- 3 Quality Assessment of 3D-Synthesized Images -- 3.1 Introduction -- 3.2 Methodology -- 3.2.1 NSS-Based NR 3D-Synthesized Image QA -- 3.2.2 Transform Domain-Based NR 3D-Synthesized Image QA -- 3.2.3 Structure Variation-Based NR 3D-Synthesized Image QA -- 3.3 Comparison and Analysis of Algorithm Performance -- 3.3.1 DIBR-Synthesized Image Database -- 3.3.2 Performance Comparison and Analysis -- 3.4 Conclusion -- References -- 4 Quality Assessment of Sonar Images -- 4.1 Introduction -- 4.2 Methodology -- 4.2.1 Full-Reference QA of Sonar Images -- 4.2.2 Semi-Reference QA of Sonar Images -- 4.2.3 Partial-Reference QA of Sonar Images -- 4.2.4 No-Reference QA of Sonar Images -- 4.3 Comparison and Analysis of Algorithm Performance -- 4.3.1 The Sonar Image Database -- 4.3.2 Performance Comparison and Analysis -- 4.4 Conclusion -- References -- 5 Quality Assessment of Enhanced Images -- 5.1 Introduction -- 5.2 Methodology -- 5.2.1 Database Set-Up -- 5.2.2 Objective QA of Enhanced Images.5.2.3 Enhanced Image QA Based on the Enhancement Technology -- 5.3 Comparison and Analysis of Algorithm Performance -- 5.3.1 CCID 2014 Database -- 5.3.2 Performance Comparison and Analysis -- 5.4 Conclusion -- References -- 6 Quality Assessment of Light-Field Image -- 6.1 Introduction -- 6.2 Methodology -- 6.2.1 FR QA of LF Images -- 6.2.2 RR QA of LF Images -- 6.2.3 NR LF Image QA Based on Spatial-Angular Measurement -- 6.2.4 Tensor Oriented NR LF Image QA -- 6.3 Comparison and Analysis of Algorithm Performance -- 6.3.1 Elaborated SMART Database -- 6.3.2 Performance Comparison and Analysis -- 6.4 Conclusion -- References -- 7 Quality Assessment of Virtual Reality Images -- 7.1 Introduction -- 7.2 Methodology -- 7.2.1 Subjective QA of VR Images -- 7.2.2 Objective QA of VR Images -- 7.2.3 Subjective-Objective QA of VR Images -- 7.2.4 Cross-Reference Stitching QA -- 7.3 Comparison and Analysis of Algorithm Performance -- 7.3.1 Performance Comparison and Analysis -- 7.4 Conclusion -- References -- 8 Quality Assessment of Super-Resolution Images -- 8.1 Introduction -- 8.2 Methodology -- 8.2.1 Creation of the QA Database for SR Image -- 8.2.2 QA of SR Image Based on Deep Learning -- 8.2.3 Natural Statistics-Based SR Image QA -- 8.3 Comparison and Analysis of Algorithm Performance -- 8.3.1 Performance Comparison and Analysis -- 8.4 Conclusion -- References.Advances in computer vision and pattern recognition.Computer graphicsComputer visionImage processingComputer graphics.Computer vision.Image processing.006.6869Gu Ke1262570Liu HongyanZhou ChengxuMiAaPQMiAaPQMiAaPQBOOK9910619267603321Quality assessment of visual content3041738UNINA