An error bound of relative image blur analysis

Sheng Wen Shih, Po Shan Kao, Wei Shin Guo

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

3 Citations (Scopus)

Abstract

A lower bound of the relative image blur estimation error of a pair of images is derived analytically in this paper. This error analysis result shows that the optimal camera parameters for obtaining the most accurate depth from defocusing (DFD) results are strongly related to the object depth. Therefore, DFD methods using only two images usually cannot achieve the most accurate depth estimates. Instead of using only two images, a sequence of images focused at different depths should be provided in order to obtain accurate DFD results. With some prior knowledge of the object depth, the derived error bound is used to select optimal image pairs from the input image sequence for computing DFD. Real experimental results show that the resulting DFD method outperforms both a DFF method and a DFD method using two images.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages100-103
Number of pages4
DOIs
Publication statusPublished - 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

Conference

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

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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