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Regularized Image Restoration by Means of Fusion for Digital Auto Focusing

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3802))

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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.

This work was supported by Korean Ministry of Science and Technology under the National Research Laboratory Project and by Korean Ministry of Information and Communication under the Chung-Ang University HNRC-ITRC program.

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© 2005 Springer-Verlag Berlin Heidelberg

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Maik, V., Shin, J., Paik, J. (2005). Regularized Image Restoration by Means of Fusion for Digital Auto Focusing. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596981_137

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  • DOI: https://doi.org/10.1007/11596981_137

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30819-5

  • Online ISBN: 978-3-540-31598-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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