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Perceptually Optimized Coded Apertures for Defocus Deblurring
Author(s) -
Masia Belen,
Presa Lara,
Corrales Adrian,
Gutierrez Diego
Publication year - 2012
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/j.1467-8659.2012.03067.x
Subject(s) - deblurring , computer science , artificial intelligence , computer vision , observer (physics) , metric (unit) , image quality , image (mathematics) , image restoration , image processing , operations management , physics , quantum mechanics , economics
The field of computational photography, and in particular the design and implementation of coded apertures, has yielded impressive results in the last years. In this paper we introduce perceptually optimized coded apertures for defocused deblurring. We obtain near‐optimal apertures by means of optimization, with a novel evaluation function that includes two existing image quality perceptual metrics. These metrics favour results where errors in the final deblurred images will not be perceived by a human observer. Our work improves the results obtained with a similar approach that only takes into account the L2 metric in the evaluation function .