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An Objective Deghosting Quality Metric for HDR Images
Author(s) -
Tursun Okan Tarhan,
Akyüz Ahmet Oğuz,
Erdem Aykut,
Erdem Erkut
Publication year - 2016
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12818
Subject(s) - computer science , metric (unit) , artifact (error) , high dynamic range , artificial intelligence , set (abstract data type) , computer vision , range (aeronautics) , process (computing) , quality (philosophy) , pattern recognition (psychology) , dynamic range , philosophy , operations management , materials science , epistemology , economics , composite material , programming language , operating system
Reconstructing high dynamic range (HDR) images of a complex scene involving moving objects and dynamic backgrounds is prone to artifacts. A large number of methods have been proposed that attempt to alleviate these artifacts, known as HDR deghosting algorithms. Currently, the quality of these algorithms are judged by subjective evaluations, which are tedious to conduct and get quickly outdated as new algorithms are proposed on a rapid basis. In this paper, we propose an objective metric which aims to simplify this process. Our metric takes a stack of input exposures and the deghosting result and produces a set of artifact maps for different types of artifacts. These artifact maps can be combined to yield a single quality score. We performed a subjective experiment involving 52 subjects and 16 different scenes to validate the agreement of our quality scores with subjective judgements and observed a concordance of almost 80%. Our metric also enables a novel application that we call as hybrid deghosting, in which the output of different deghosting algorithms are combined to obtain a superior deghosting result.