Abstract
Decoupling shading and reflectance from complex scene-images is a long-standing problem in computer vision. We introduce a framework for decomposing an image into the product of an illumination component and a reflectance component. Due to the ill-posed nature of the problem, prior information on shading and reflectance is mandatory. The proposed method adopts the premise that pixels in a region with similar chromaticity values should have the same reflectance. This assumption was used to minimize the l2 norm of the local per-pixel reflectance gradients to extract the shading and reflectance components. To obtain smooth chromatic regions, texture was treated in a new style. Texture was removed in the first step of the algorithm and the smooth image was processed for intrinsic decomposition. In the final step, texture details were added to the intrinsic components based on the material of each pixel. In addition, user-assistance was used to further refine the results. The qualitative and quantitative evaluation on the MIT intrinsic dataset indicated that the quality of intrinsic image decomposition was improved in comparison with previous methods.
Highlights
Intrinsic image components can be regarded as a set of images describing an image in terms of scene illumination, shape and reflectance of surfaces in the scene
Our method was based on the assumption that pixels in a region with similar chromaticity share the same reflectance value
The reflectance component was obtained by minimizing an energy function which defined the reflectance value of a pixel as the weighted sum of reflectance values of pixels obtained by region growing the current pixel
Summary
Intrinsic image components can be regarded as a set of images describing an image in terms of scene illumination, shape and reflectance of surfaces in the scene. Decomposing an image into its intrinsic components has a wide range of applications in industry. Eliminating the shading component provides illumination-free models that could be used for relighting [1], retexturing [2, 3], gray scale colorization [4], and reflectance editing [5]. The process of recovering shading and reflectance can be accomplished by two approaches: using a single image or multiple images. Employing depth information and image sequences for deriving intrinsic components have been considered in many studies. It is convenient to aid intrinsic image decomposition through user-assistance. Additional information contributes to the improvement of intrinsic image
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