Just noticeable defocus blur detection and estimation
Refereed conference paper presented and published in conference proceedings


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AbstractWe tackle a fundamental problem to detect and estimate just noticeable blur (JNB) caused by defocus that spans a small number of pixels in images. This type of blur is common during photo taking. Although it is not strong, the slight edge blurriness contains informative clues related to depth. We found existing blur descriptors based on local information cannot distinguish this type of small blur reliably from unblurred structures. We propose a simple yet effective blur feature via sparse representation and image decomposition. It directly establishes correspondence between sparse edge representation and blur strength estimation. Extensive experiments manifest the generality and robustness of this feature.
All Author(s) ListShi J., Xu L., Jia J.
Name of ConferenceIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Start Date of Conference07/06/2015
End Date of Conference12/06/2015
Place of ConferenceBoston
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IEEE,
Year2015
Month10
Day14
Volume Number07-12-June-2015
Pages657 - 665
ISBN9781467369640
ISSN1063-6919
LanguagesEnglish-United Kingdom

Last updated on 2020-31-07 at 23:10