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Regularized Image Restoration by Means of Fusion for Digital Auto Focusing.

Authors :
Yue Hao
Jiming Liu
Yu-Ping Wang
Yiu-ming Cheung
Hujun Yin
Licheng Jiao
Jianfeng Ma
Yong-Chang Jiao
Vivek Maik
Jeongho Shin
Joonki Paik
Source :
Computational Intelligence & Security (9783540308195); 2005, p929-934, 6p
Publication Year :
2005

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540308195
Database :
Supplemental Index
Journal :
Computational Intelligence & Security (9783540308195)
Publication Type :
Book
Accession number :
32885833
Full Text :
https://doi.org/10.1007/11596981_137