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Depth from defocus by changing camera aperture: a spatial domain approach

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

65 Scopus citations

Abstract

This paper describes the application of a new Spatial-Domain Convolution/ Deconvolution transform (S transform) for determining distance of objects using image defocus. The method known as STMAP involves simple local operations on only two images taken with different aperture diameters and can be easily implemented in parallel. Both images can be arbitrarily blurred and neither of them needs to be a focused image taken with a pin-hole camera. STMAP has been implemented on an actual camera system named SPARCS. EXperimental results on a real-world planar objects are presented. The results indicate that STMAP is useful in practical applications. The utility of the method is demonstrated for rapid autofocusing of electronic cameras. STMAP is computationally more efficient than other Depth-from-Focus methods and the results are comparable to a Fourier Transform based approach.

Original languageEnglish
Title of host publicationIEEE Computer Vision and Pattern Recognition
Editors Anon
PublisherPubl by IEEE
Pages61-67
Number of pages7
ISBN (Print)0818638826
StatePublished - 1993
EventProceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - New York, NY, USA
Duration: Jun 15 1993Jun 18 1993

Publication series

NameIEEE Computer Vision and Pattern Recognition

Conference

ConferenceProceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CityNew York, NY, USA
Period06/15/9306/18/93

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