Specular highlight reduction with known surface geometry

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The separation of reflection components is an important issue in computer graphics, computer vision, and image processing. This is a highly ill-posed problem since the number of unknowns to solve is much larger than the number of equations. We present a method to reduce the difficulty of this problem by assuming that surface geometry is known. A novel objective function based on robust principal component analysis is proposed to simultaneously separate specularities and estimate the position of light source. We develop an Augmented Lagrangian Multiplier based algorithm to solve the objective function efficiently and effectively. Experimental results on real-world and synthetic data demonstrate the effectiveness of our method.

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论文评审过程:Received 31 January 2017, Revised 3 October 2017, Accepted 18 October 2017, Available online 27 October 2017, Version of Record 19 March 2018.

论文官网地址:https://doi.org/10.1016/j.cviu.2017.10.010