Visible Light Spectrum Extraction from Diffraction Images by Deconvolution and the Cepstrum

Show simple item record Toivonen, Mikko Evert Talvitie, Topi Rajani, Chang Klami, Arto 2021-09-16T08:45:02Z 2021-09-16T08:45:02Z 2021-09
dc.identifier.citation Toivonen , M E , Talvitie , T , Rajani , C & Klami , A 2021 , ' Visible Light Spectrum Extraction from Diffraction Images by Deconvolution and the Cepstrum ' , Journal of Imaging , vol. 7 , no. 9 , 166 .
dc.identifier.other PURE: 168476638
dc.identifier.other PURE UUID: 57103a8a-0f7e-4ebc-bf4a-62995c91ec87
dc.identifier.other ORCID: /0000-0002-7950-1355/work/100083688
dc.identifier.other ORCID: /0000-0003-1691-8206/work/100084708
dc.identifier.other WOS: 000699542900001
dc.description.abstract Accurate color determination in variable lighting conditions is difficult and requires special devices. We considered the task of extracting the visible light spectrum using ordinary camera sensors, to facilitate low-cost color measurements using consumer equipment. The approach uses a diffractive element attached to a standard camera and a computational algorithm for forming the light spectrum from the resulting diffraction images. We present two machine learning algorithms for this task, based on alternative processing pipelines using deconvolution and cepstrum operations, respectively. The proposed methods were trained and evaluated on diffraction images collected using three cameras and three illuminants to demonstrate the generality of the approach, measuring the quality by comparing the recovered spectra against ground truth measurements collected using a hyperspectral camera. We show that the proposed methods are able to reconstruct the spectrum, and, consequently, the color, with fairly good accuracy in all conditions, but the exact accuracy depends on the specific camera and lighting conditions. The testing procedure followed in our experiments suggests a high degree of confidence in the generalizability of our results; the method works well even for a new illuminant not seen in the development phase. en
dc.format.extent 25
dc.language.iso eng
dc.relation.ispartof Journal of Imaging
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.subject spectrum
dc.subject spectrometer
dc.subject cepstrum
dc.subject deconvolution
dc.subject diffraction imaging
dc.title Visible Light Spectrum Extraction from Diffraction Images by Deconvolution and the Cepstrum en
dc.type Article
dc.contributor.organization Department of Computer Science
dc.contributor.organization Helsinki Institute for Information Technology
dc.contributor.organization Multi-source probabilistic inference research group / Arto Klami
dc.description.reviewstatus Peer reviewed
dc.relation.issn 2313-433X
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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