Regularized image restoration by means of fusion for digital auto focusing

Authors:
Vivek Maik;Jeongho Shin;Joonki Paik
Affiliations:
Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film Chung-Ang University, Seoul, Korea;Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film Chung-Ang University, Seoul, Korea
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

Citing 3
Cited 1

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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.