COMPUTATIONAL FILTER-APERTURE APPROACH FOR SINGLE-VIEW MULTI-FOCUSING

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초록

Most of the focusing techniques need to estimate depth information for ensuring that the object of interest is at an appropriate distance for full frontal focus. Computational cameras which can variably focus different regions of the scene with large depth of field have been proposed. In this paper we propose a full auto-focusing algorithm using computational camera without involving any digital image restoration methods and just one input. The proposed computational camera uses multiple filter apertures corresponding to each color channel which can acquire three shifted views of a scene in the RGB color planes. We can make any region focused by appropriately shifting each color channel to be aligned. Depth map estimation is carried out to extract different regions from these channel shifted images which is later fused to produce the final image without any focal blur. Experimental results show performance and feasibility of the proposed algorithm for auto-focusing images with one or more differently out-of-focused objects.

키워드

Image restoration; image classification
제목
COMPUTATIONAL FILTER-APERTURE APPROACH FOR SINGLE-VIEW MULTI-FOCUSING
저자
Maik, Vivek; Cho, Dohee; Kim, Sangjin; Har, Donghwan; Paik, Joonki
DOI
10.1109/ICIP.2009.5414519
발행일
2009-11
유형
Proceedings Paper
저널명
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6
페이지
1541 ~ 1544