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Focused image recovery from two defocused images recorded with different camera settings

  • Stony Brook University

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

5 Scopus citations

Abstract

Two new methods are presented for recovering the focused image of an object from only two blurred images recorded with different camera parameter settings. First a blur parameter σ is estimated using one of our two recently proposed depth-from-defocus methods. Then one of the two blurred images is deconvolved to recover the focused image. The first method requires only the knowledge of σ of the camera's point spread function (PSF). It is based on a new spatial domain convolution/ deconvolution transform. The second method requires full knowledge of the form of the PSF and is estimated using step edges. The focused image is obtained through deconvolution in the Fourier Domain using the Wiener filter. For both methods, results of experiments on actual defocused images recorded by a CCD camera are presented. The first method requires less computation and gives satisfactory results for up to medium levels of blur. The second method gives good results for up to relatively high levels of blur.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherPubl by IEEE
Pages786-791
Number of pages6
ISBN (Print)081863880X, 081863880X, 9780818658273
DOIs
StatePublished - 1994
EventProceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Seattle, WA, USA
Duration: Jun 21 1994Jun 23 1994

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

ConferenceProceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CitySeattle, WA, USA
Period06/21/9406/23/94

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