On the performance of objective quality metrics for lightfields

2021 ◽  
Vol 93 ◽  
pp. 116179
Author(s):  
Saeed Mahmoudpour ◽  
Peter Schelkens
Keyword(s):  
Quality Metrics ◽  
Objective Quality

A Benchmark of Objective Quality Metrics for HLG-Based HDR/WCG Image Coding

2020 ◽  
Author(s):  
Yasuko Sugito ◽  
Trevor Canham ◽  
Javier Vazquez-Corral ◽  
Marcelo Bertalmio
Keyword(s):  
Image Coding ◽  
Quality Metrics ◽  
Objective Quality

The quest for 'diagnostically lossless' medical image compression: a comparative study of objective quality metrics for compressed medical images

2014 ◽  
Author(s):  
Ilona Kowalik-Urbaniak ◽  
Dominique Brunet ◽  
Jiheng Wang ◽  
David Koff ◽  
Nadine Smolarski-Koff ◽  
...  
Keyword(s):  
Image Compression ◽  
Comparative Study ◽  
Medical Image ◽  
Medical Images ◽  
Quality Metrics ◽  
Medical Image Compression ◽  
Objective Quality

scholarly journals Voronoi-based Objective Quality Metrics for Omnidirectional Video

2019 ◽  
Author(s):  
Simone Croci ◽  
Cagri Ozcinar ◽  
Emin Zerman ◽  
Julian Cabrera ◽  
Aljosa Smolic
Keyword(s):  
Quality Metrics ◽  
Objective Quality

scholarly journals Perceptually Motivated Method for Image Inpainting Comparison

2019 ◽  
Author(s):  
Иван Молодецких ◽  
Ivan Molodetskikh ◽  
Михаил Ерофеев ◽  
Mikhail Erofeev ◽  
Дмитрий Ватолин ◽  
...  
Keyword(s):  
Image Quality ◽  
Standard Method ◽  
Image Inpainting ◽  
Human Perception ◽  
Quality Metrics ◽  
Future Research ◽  
Image Quality Metrics ◽  
Objective Quality

The field of automatic image inpainting has progressed rapidly in recent years, but no one has yet proposed a standard method of evaluating algorithms. This absence is due to the problem’s challenging nature: image-­inpainting algorithms strive for realism in the resulting images, but realism is a subjective concept intrinsic to human perception. Existing objective image-­quality metrics provide a poor approximation of what humans consider more or less realistic. To improve the situation and to better organize both prior and future research in this field, we conducted a subjective comparison of nine state-­of­-the­-art inpainting algorithms and propose objective quality metrics that exhibit high correlation with the results of our comparison.

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