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A Variational Approach to Recovering Depth From Defocused Images
October 1997 (vol. 19 no. 10)
pp. 1158-1164

Abstract—In this paper, we propose a regularized solution to the depth from defocus (DFD) problem using the space-frequency representation (SFR) framework. A smoothness constraint is imposed on the estimates of the blur parameter, and a variational approach to the DFD problem is developed. Among the numerous SFRs, we study the applicability of the complex spectrogram and the Wigner distribution, in particular, for depth recovery. The performance of the proposed variational method is tested on both synthetic and real images. The method yields good results, and the quality of the estimates is significantly better than that obtained without the smoothness constraint on the blur parameter.

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Index Terms:
Depth from defocus, space-variant blur, complex spectrogram, Wigner distribution, space-variant filtering, regularization, Euler equation.
Citation:
A.n. Rajagopalan, S. Chaudhuri, "A Variational Approach to Recovering Depth From Defocused Images," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 10, pp. 1158-1164, Oct. 1997, doi:10.1109/34.625126
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