Deriving Intrinsic Images from Image Sequences

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Deriving Intrinsic Images from Image Sequences
Intrinsic images are a useful midlevel description of scenes proposed by Barrow and Tenenbaum [1]. An image is decomposed into two images: a reflectance image and an illumination image. Finding such a decomposition remains a difficult problem in computer vision. Here we focus on a slightly easier problem: given a sequence of images where the reflectance is constant and the illumination changes, can we recover illumination images and a single reflectance image? We show that this problem is still illposed and suggest approaching it as a maximum-likelihood estimation problem. Following recent work on the statistics of natural images, we use a prior that assumes that illumination images will give rise to sparse filter outputs. We show that this leads to a simple, novel algorithm for recovering reflectance images. We illustrate the algorithm's performance on real and synthetic image sequences. In: Proc ICCV (2001)
Yair Weiss
Added 15 Oct 2009
Updated 31 Oct 2009
Type Conference
Year 2001
Where ICCV
Authors Yair Weiss
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