DocumentCode :
1305474
Title :
Shadow Removal Using Intensity Surfaces and Texture Anchor Points
Author :
Arbel, Eli ; Hel-Or, Hagit
Author_Institution :
Dept. of Comput. Sci., Univ. of Haifa, Haifa, Israel
Volume :
33
Issue :
6
fYear :
2011
fDate :
6/1/2011 12:00:00 AM
Firstpage :
1202
Lastpage :
1216
Abstract :
Removal of shadows from a single image is a challenging problem. Producing a high-quality shadow-free image which is indistinguishable from a reproduction of a true shadow-free scene is even more difficult. Shadows in images are typically affected by several phenomena in the scene, including physical phenomena such as lighting conditions, type and behavior of shadowed surfaces, occluding objects, etc. Additionally, shadow regions may undergo postacquisition image processing transformations, e.g., contrast enhancement, which may introduce noticeable artifacts in the shadow-free images. We argue that the assumptions introduced in most studies arise from the complexity of the problem of shadow removal from a single image and limit the class of shadow images which can be handled by these methods. The purpose of this paper is twofold: First, it provides a comprehensive survey of the problems and challenges which may occur when removing shadows from a single image. In the second part of the paper, we present our framework for shadow removal, in which we attempt to overcome some of the fundamental problems described in the first part of the paper. Experimental results demonstrating the capabilities of our algorithm are presented.
Keywords :
image enhancement; image texture; contrast enhancement; image processing transformations; intensity surfaces; shadow free image; shadow removal; texture anchor points; Geometry; Image reconstruction; Light sources; Lighting; Pixel; Surface texture; Surface treatment; Shadow removal; color; enhancement.; region growing; shading; shadow detection; texture; Algorithms; Artifacts; Artificial Intelligence; Humans; Image Enhancement; Image Processing, Computer-Assisted; Lighting; Pattern Recognition, Automated;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2010.157
Filename :
5557880
Link To Document :
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