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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Maik, V., Shin, J., & Paik, J. (2005). Regularized image restoration by means of fusion for digital auto focusing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3802 LNAI, pp. 929–934). https://doi.org/10.1007/11596981_137
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