Decomposing 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.



@article{Garces2012, author = {Garces, Elena and Munoz, Adolfo and Lopez-Moreno, Jorge and Gutierrez, Diego}, title = {Intrinsic Images by Clustering}, journal = {Computer Graphics Forum (Proc. EGSR 2012)}, year = {2012}, volume = {31}, number = {4}, }