Single-image, spatially variant, out-of-focus blur removal

Stanley H. Chan; Truong Q. Nguyen

doi:10.1117/12.929924

19 October 2012 Single-image, spatially variant, out-of-focus blur removal

Stanley H. Chan, Truong Q. Nguyen

Proceedings Volume 8500, Image Reconstruction from Incomplete Data VII; 85000F (2012) https://doi.org/10.1117/12.929924
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

This paper addresses the problem of two-layer out-of-focus blur removal from a single image, in which either the foreground or the background is in focus while the other is out of focus. To recover details from the blurry parts, the existing blind deconvolution algorithms are insufficient as the problem is spatially variant. The proposed method exploits the invariant structure of the problem by first predicting the occluded background. Then a blind deconvolution algorithm is applied to estimate the blur kernel and a coarse estimate of the image is found as a side product. Finally, the blurred region is recovered using total variation minimization, and fused with the sharp region to produce the final deblurred image.

Citation Download Citation

Stanley H. Chan and Truong Q. Nguyen "Single-image, spatially variant, out-of-focus blur removal", Proc. SPIE 8500, Image Reconstruction from Incomplete Data VII, 85000F (19 October 2012); https://doi.org/10.1117/12.929924

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