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Báo cáo hóa học: " Research Article A Practical Approach for Simultaneous Estimation of Light Source Position, Scene Structure, and Blind Restoration Using Photometric Observations"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Practical Approach for Simultaneous Estimation of Light Source Position, Scene Structure, and Blind Restoration Using Photometric Observations | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 785364 12 pages doi 10.1155 2008 785364 Research Article A Practical Approach for Simultaneous Estimation of Light Source Position Scene Structure and Blind Restoration Using Photometric Observations Swati Sharma1 2 and Manjunath V. Joshi1 3 1 Laboratoire d Imagerie et de Neurosciences Cognitives UMR CNRS-ULP 7191 67000 Strasbourg France 2Laboratoire des Sciences de l Image de l Informatique etde la Teledetection UMR CNRS-ULP 7005 67412 Illkirch Cedex France 3 Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar 382007 Gujarat India Correspondence should be addressed to Swati Sharma swati.sharma@linc.u-strasbg.fr Received 26 September 2007 Revised 15 February 2008 Accepted 2 April 2008 Recommended by Hubert Cardot Given blurred observations of a stationary scene captured using a static camera but with different and unknown light source positions we estimate the light source positions and scene structure surface gradients and perform blind image restoration. The images are restored using the estimated light source positions surface gradients and albedo. The surface of the object is assumed to be Lambertian. We first propose a simple approach to obtain a rough estimate of the light source position from a single image using the shading information which does not use any calibration or initialization. We model the prior information for the scene structure as a separate Markov random field MRF with discontinuity preservation and the blur function is modeled as Gaussian. A proper regularization approach is then used to estimate the light source position scene structure and blur parameter. The optimization is carried out using the graph cuts approach. The advantage of the proposed approach is that its time complexity is much less as compared to other approaches that use global optimization techniques such as simulated annealing. Reducing the