Intrinsic Images by Clustering

dc.contributor.authorGarces, Elenaen_US
dc.contributor.authorMunoz, Adolfoen_US
dc.contributor.authorLopez-Moreno, Jorgeen_US
dc.contributor.authorGutierrez, Diegoen_US
dc.contributor.editorFredo Durand and Diego Gutierrezen_US
dc.description.abstractDecomposing an input image into its intrinsic shading and reflectance components is a long-standing ill-posed problem. We present a novel algorithm that requires no user strokes and works on a single image. Based on simple assumptions about its reflectance and luminance, we first find clusters of similar reflectance in the image, and build a linear system describing the connections and relations between them. Our assumptions are less restrictive than widely-adopted Retinex-based approaches, and can be further relaxed in conflicting situations. The resulting system is robust even in the presence of areas where our assumptions do not hold. We show a wide variety of results, including natural images, objects from the MIT dataset and texture images, along with several applications, proving the versatility of our method.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationen_US
dc.titleIntrinsic Images by Clusteringen_US