top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.

Biblioteca

MARC Lista (tabellare)
Quality assessment of visual content / / Ke Gu, Hongyan Liu and Chengxu Zhou
Quality assessment of visual content / / Ke Gu, Hongyan Liu and Chengxu Zhou
Autore Gu Ke
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (256 pages)
Disciplina 006.6869
Collana Advances in computer vision and pattern recognition
Soggetto topico Computer graphics
Computer vision
Image processing
ISBN 981-19-3347-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNINA-9910619267603321
Gu Ke  
Singapore : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Quality assessment of visual content / / Ke Gu, Hongyan Liu and Chengxu Zhou
Quality assessment of visual content / / Ke Gu, Hongyan Liu and Chengxu Zhou
Autore Gu Ke
Pubbl/distr/stampa Singapore : , : Springer, , [2022]
Descrizione fisica 1 online resource (256 pages)
Disciplina 006.6869
Collana Advances in computer vision and pattern recognition
Soggetto topico Computer graphics
Computer vision
Image processing
ISBN 981-19-3347-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto 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.
Record Nr. UNISA-996495561703316
Gu Ke  
Singapore : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui