000162255 001__ 162255 000162255 005__ 20251017144547.0 000162255 0247_ $$2doi$$a10.1111/cgf.12717 000162255 0248_ $$2sideral$$a93967 000162255 037__ $$aART-2016-93967 000162255 041__ $$aeng 000162255 100__ $$aAlvarez-Cortes, Sara 000162255 245__ $$aPractical Low-Cost Recovery of Spectral Power Distributions 000162255 260__ $$c2016 000162255 5060_ $$aAccess copy available to the general public$$fUnrestricted 000162255 5203_ $$aMeasuring the spectral power distribution of a light source, that is, the emission as a function of wavelength, typically requires the use of spectrophotometers or multi-spectral cameras. Here, we propose a low-cost system that enables the recovery of the visible light spectral signature of different types of light sources without requiring highly complex or specialized equipment and using just off-the-shelf, widely available components. To do this, a standard Digital Single-Lens Reflex (DSLR) camera and a diffraction filter are used, sacrificing the spatial dimension for spectral resolution. We present here the image formation model and the calibration process necessary to recover the spectrum, including spectral calibration and amplitude recovery. We also assess the robustness of our method and perform a detailed analysis exploring the parameters influencing its accuracy. Further, we show applications of the system in image processing and rendering. Measuring the spectral power distribution of a light source, that is, the emission as a function of wavelength, typically requires the use of spectrophotometers or multi-spectral cameras. Here, we propose a low-cost system that enables the recovery of the visible light spectral signature of different types of light sources without requiring highly complex or specialized equipment and using just off-the-shelf, widely available components. To do this, a standard DSLR camera and a diffraction filter are used, sacrificing the spatial dimension for spectral resolution. We present here the image formation model and the calibration process necessary to recover the spectrum, including spectral calibration and amplitude recovery. 000162255 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/ 000162255 590__ $$a1.611$$b2016 000162255 591__ $$aCOMPUTER SCIENCE, SOFTWARE ENGINEERING$$b44 / 106 = 0.415$$c2016$$dQ2$$eT2 000162255 592__ $$a0.732$$b2016 000162255 593__ $$aComputer Networks and Communications$$c2016$$dQ1 000162255 593__ $$aComputer Graphics and Computer-Aided Design$$c2016$$dQ1 000162255 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000162255 700__ $$aKunkel, Timo 000162255 700__ $$0(orcid)0000-0003-0060-7278$$aMasia, Belen$$uUniversidad de Zaragoza 000162255 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf. 000162255 773__ $$g35, 1 (2016), 166-178$$pComput. graph. forum$$tComputer Graphics Forum$$x0167-7055 000162255 8564_ $$s10957170$$uhttps://zaguan.unizar.es/record/162255/files/texto_completo.pdf$$yPostprint 000162255 8564_ $$s2016069$$uhttps://zaguan.unizar.es/record/162255/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000162255 909CO $$ooai:zaguan.unizar.es:162255$$particulos$$pdriver 000162255 951__ $$a2025-10-17-14:10:16 000162255 980__ $$aARTICLE