Abstract
This paper proposes a novel digital auto-focusing algorithm using image fusion, which restores an out-of-focus image with multiple, differently out-of-focus objects. The proposed auto-focusing algorithm consists of (i) building a prior set of point spread functions (PSFs), (ii) image restoration, and (iii) fusion of the restored images. Instead of designing an image restoration filter for multi-object auto-focusing, we propose an image fusion-based auto-focusing algorithm by fusing multiple, restored images based on prior estimated set of PSFs. The prior estimated PSFs overcome heavy computational overhead and make the algorithm suitable for real-time applications. By utilizing both redundant and complementary information provided by different images, the proposed fusion algorithm can restore images with multiple, out-of-focus objects. Experimental results show the performance of the proposed auto-focusing algorithm.
This work was supported by Korean Ministry of Science and Technology under the National Research Laboratory Project, by Korean Ministry of Information and Communication under the Chung-Ang University HNRC-ITRC program, and by the Korea Research Foundation Grant funded by Korean Government (MOEHRD)(R08-2004-000-10626-0).
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© 2005 Springer-Verlag Berlin Heidelberg
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Shin, J., Maik, V., Lee, J., Paik, J. (2005). Multi-object Digital Auto-focusing Using Image Fusion. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2005. Lecture Notes in Computer Science, vol 3708. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558484_26
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DOI: https://doi.org/10.1007/11558484_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29032-2
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