caa a22 4500 606209778 CHVBK 20210128101030.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s11220-015-0105-4 doi (NATIONALLICENCE)springer-10.1007/s11220-015-0105-4 Multi-Focus Raw Bayer Pattern Image Fusion for Single-Chip Camera [Elektronische Daten] [Bin Yang, Jibin Chen] In this paper, an efficient patch-based image fusion approach for raw images of single-chip imaging devices incorporated with the Bayer CFA pattern is presented. The multi-source raw Bayer pattern images are firstly parted into half overlapped patches. Then, the patches with maximum clarity measurement defined for raw Bayer pattern image are selected as the fused patches. Next, all the fused local patches are merged with weighted average method in order to reduce the blockness effect of fused raw Bayer pattern image. Finally, the real color fused image is obtained by gradient based demosaicing technology. The multi-source raw Bayer pattern data is fused before demosaicing, so that the multi-sensor system will be more efficient and the artifacts introduced in demosaicing processing do not accumulate in image fusion processing. For comparison, the raw images are also interpolated firstly, and then various image fusion methods are used to get the fused color images. Experimental results show that the proposed algorithm is valid and very effective. Springer Science+Business Media New York, 2015 Image fusion nationallicence Demosaicing nationallicence Clarity measurement nationallicence Bayer pattern nationallicence Yang Bin College of Electric Engineering, University of South China, 421001, Hengyang, China aut Chen Jibin College of Electric and Information Engineering, Zhengzhou University of Light Industry, 450002, Zhengzhou, China aut Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-14 1557-2064 16:1<1 2015 16 11220 https://doi.org/10.1007/s11220-015-0105-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11220-015-0105-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yang Bin College of Electric Engineering, University of South China, 421001, Hengyang, China aut NATIONALLICENCE 700 1- Chen Jibin College of Electric and Information Engineering, Zhengzhou University of Light Industry, 450002, Zhengzhou, China aut NATIONALLICENCE 773 0- Sensing and Imaging Springer US; http://www.springer-ny.com 16/1(2015-12-01), 1-14 1557-2064 16:1<1 2015 16 11220