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HDR Image and Video Quality Prediction
, P. Le Callet, G. Valenzise, F. De Simone, F. Dufaux, R.K. Mantiuk
Published in Elsevier Inc.
Pages: 455 - 473
Objective quality assessment methods use a computational (mathematical) model to provide estimates of subjective video quality. While such objective models may not mimic subjective opinions accurately in a general scenario, they can be reasonably effective in specific conditions/applications. Hence, they can be an important tool toward automating the testing and standardization of high dynamic range (HDR) video processing algorithms, especially when subjective tests may not be feasible. Therefore, this chapter deals with objective quality assessment of HDR content and elaborates on the issues and challenges that arise. We also discuss and present details of the existing efforts on the topic. Particularly, the focus is on full-reference HDR metrics which take as input two HDR signals (one of them is always assumed to be the reference). Hence, in the context of this chapter, the term "quality" can also be interpreted as "fidelity," and both can be used interchangeably. Another use case is that of comparing HDR and low dynamic range signals, and this is needed, for instance, when HDR content is tone-mapped to be rendered on a low dynamic range display. © 2016 Elsevier Ltd All rights reserved.
About the journal
JournalData powered by TypesetHigh Dynamic Range Video: From Acquisition to Display and Applications
PublisherData powered by TypesetElsevier Inc.