Generating omnifocus images using graph cuts and a new focus measure

Ning Xu, Karhan Tan, Himanshu Arora, Narendra Ahuja

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we discuss how to generate omnifocus images from a sequence of different focal setting images. We first show that the existing focus measures would encounter difficulty when detecting which frame is most focused for pixels in the regions between intensity edges and uniform areas. Then we propose a new focus measure that could be used to handle this problem. In addition, after computing focus measures for every pixel in all images, we construct a three dimensional (3D) node-capacitated graph and apply a graph cut based optimization method to estimate a spatio-focus surface that minimizes the summation of the new focus measure values on this surface. An omnifocus image can be directly generated from this minimal spatiofocus surface. Experimental results with simulated and real scenes are provided.

Original languageEnglish (US)
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages697-700
Number of pages4
DOIs
StatePublished - Dec 20 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume4
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period8/23/048/26/04

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Xu, N., Tan, K., Arora, H., & Ahuja, N. (2004). Generating omnifocus images using graph cuts and a new focus measure. In J. Kittler, M. Petrou, & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 (pp. 697-700). (Proceedings - International Conference on Pattern Recognition; Vol. 4). https://doi.org/10.1109/ICPR.2004.1333868