The image may be partially blurred because of defocus, shaking camera or moving object. In this paper, we introduce a novel method to extract the blurred area automatically, which mainly consists of two stages: coarse detection and fine extraction. In the coarse detection, we proposed a block-based blurred/sharp area detection algorithm which roughly divides the image into blurred, sharp and undefined blocks. Both the spatial gradient statistics and the frequential power spectrum are used as blur metrics in the algorithm. For the fine extraction, we introduce an improved lazy snapping which takes blurred and sharp blocks of the coarse detection as the seeds for automatic lazy snapping and thus extracts the blurred area automatically. Experimental results prove that the efficiency of the proposed method.

Date Published: 12 January 2012
PDF: 7 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501F (12 January 2012); doi: 10.1117/12.921793

Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)