Abstract
This paper presents a method for fusing multiple images of a static scene and shows how to apply the proposed method to extend depth of field. Pattern selective image fusion provides a mechanism for combining multiple monochromatic images through identifying salient features in the source images and combining those features in to a single fused image. The source images are first decomposed using filter subtract decimate (FSD) in laplacian domain. Thesum-modified-Laplacian (SML) is used for obtaining the depth of focus in the source images. The selected images are then blended together using monotonically decreasing soft decision blending (SDB), which enables smooth transitions across region boundaries. The resulting fused image utilizes focus information that is greater than that of the constituent images, while retaining a natural verisimilitude. Experimental results show the performance of the depth of focus extension using consumer video camera outputs.
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). Pattern Selective Image Fusion for Multi-focus Image Reconstruction. In: Gagalowicz, A., Philips, W. (eds) Computer Analysis of Images and Patterns. CAIP 2005. Lecture Notes in Computer Science, vol 3691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556121_83
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DOI: https://doi.org/10.1007/11556121_83
Publisher Name: Springer, Berlin, Heidelberg
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