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Two stage based shadow removal from a single image

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Shadow detection and removal in real scene images is always a challenging but yet intriguing problem. In contrast with the rapidly expanding and continuous interests on this area, it is always hard to provide a robust system to eliminate shadows in static images. This paper aimed to give a comprehensive method to remove shadows based on a two stage approach: vague shadow estimation and hard shadow estimation. First, classification is applied to the derivatives of the input image to separate the vague shadows. Then, color invariant is exploited to distinguish the hard shadow edges from the material edges. Next, a robust shadow edge mask was obtained based on the combination of the vague and hard shadow mask. By using image reintegrating approaches, we derived the shadow estimation form the mask and obtained the shadow-free reflectance image by subtracting shadows from the original image. Experimental results showed that our method can robustly remove both vague and hard shadows appearing in the real scene images.
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Bibliografia
  • [1] J.M. Wang, Y.C. Chung, C.L. Chang, S.W. Chen, Shadow Detection and Removal for Traffic Images, Proc. IEEE International Conference on Networking, Sensing and Control, vol. 1, pp. 649 - 654, 2004.
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  • [16] G.D. Finlayson, S.D. Hordley C. Lu and M.S. Drew, On the Removal of Shadows from Images, IEEE Trans. Pattern Anal. Machine Intell., Jan, 2006
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bwmeta1.element.baztech-article-BAT5-0017-0078
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