26 January 2006 A robust algorithm for estimation of depth map for 3D shape recovery
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Abstract
Three-dimensional shape recovery from one or multiple observations is a challenging problem of computer vision. In this paper, we present a new focus measure for calculation of depth map. That depth map can further be used in techniques and algorithms leading to recovery of three dimensional structure of object which is required in many high level vision applications. The focus measure presented has shown robustness in presence of noise as compared to the earlier focus measures. This new focus measure is based on an optical transfer function using Discrete Cosine Transform and its results are compared with the earlier focus measures including Sum of Modified Laplacian (SML) and Tenenbaum focus measures. With this new focus measure, the results without any noise are almost similar in nature to the earlier focus measures however drastic improvement is observed with respect to others in the presence of noise. The proposed focus measure is applied on a test image, on a sequence of 97 simulated cone images and on a sequence of 97 real cone images. The images were added with the Gaussian noise which arises due to factors such as electronic circuit noise and sensor noise due to poor illumination and/or high temperature.
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Aamir Saeed Malik, Aamir Saeed Malik, Tae-Sun Choi, Tae-Sun Choi, } "A robust algorithm for estimation of depth map for 3D shape recovery", Proc. SPIE 6056, Three-Dimensional Image Capture and Applications VII, 605608 (26 January 2006); doi: 10.1117/12.641585; https://doi.org/10.1117/12.641585
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