Regularized image restoration by means of fusion for digital auto focusing
- Authors
- Maik, V; Shin, J; Paik, Joonki
- Issue Date
- Dec-2005
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 2, PROCEEDINGS, v.3802, pp 929 - 934
- Pages
- 6
- Journal Title
- COMPUTATIONAL INTELLIGENCE AND SECURITY, PT 2, PROCEEDINGS
- Volume
- 3802
- Start Page
- 929
- End Page
- 934
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/40221
- DOI
- 10.1007/11596981_137
- ISSN
- 0302-9743
1611-3349
- Abstract
- This paper proposes a novel digital auto-focusing algorithm using image fusion, which restores an image with out-of-focus objects. Instead of designing an image restoration filter for auto-focusing, we propose an image fusion-based auto-focusing algorithm by fusing multiple, restored images based on regularized iterative restoration. The proposed auto-focusing algorithm consists of (i) sum-modified-Laplacian (SML) for obtaining salient focus measure, (ii) iterative image restoration, (iii) auto focusing error metric (AFEM) for optimal restoration(iv) soft decision fusion and blending (SDFB) which enables smooth transition across region boundaries. By utilizing restored images at consecutive levels of iteration, the soft decision fusion and blending algorithm can restore images with multiple, out-of-focus objects. An auto-focusing error metric is used to provide an appropriate termination point for iterative restoration.
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Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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