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题名: Recovering sensor spectral sensitivity from raw data
作者: Wu DL(吴登禄) ; Tian JD(田建东) ; Li BF(李冰锋) ; Wang YN(王耀南) ; Tang YD(唐延东)
作者部门: 机器人学研究室
刊名: JOURNAL OF ELECTRONIC IMAGING
ISSN号: 1017-9909
出版日期: 2013
卷号: 22, 期号:2, 页码:1-8
收录类别: SCI ; EI
产权排序: 1
摘要: Accurate sensor spectral sensitivity (SSS) plays an important role in color reproduction, imaging, and computer vision. However, such data are not always available from manufacturers. We focus on recovering SSS from raw data, and propose a method to recover SSS. Using raw data, instead of sRGB data, to recover the SSS is due to the fact that the raw data are more closely related with actual sensor response values than sRGB data. With the raw data, the SSS can be recovered more accurately than with sRGB data that is widely used to recover SSS by almost all state-of-art recovery methods. Besides applying raw data in the recovery process, the other contribution is that we propose a new and simple cost function for the SSS recovery problem. This problem is then transformed into an optimization issue by minimizing the cost function. This minimization can be solved by a multiobject optimization method with a genetic algorithm. In contrast to the previous methods, our method is simple and has no parameter that needs to be determined by some prior knowledge. We validate our method through the experiments and comparison with the state-of-art methods under different illuminants. (c) 2013 SPIE and IS
语种: 英语
WOS记录号: WOS:000322376100046
WOS标题词: Science & Technology ; Technology ; Physical Sciences
类目[WOS]: Engineering, Electrical & Electronic ; Optics ; Imaging Science & Photographic Technology
关键词[WOS]: COLOR ; IMAGE
研究领域[WOS]: Engineering ; Optics ; Imaging Science & Photographic Technology
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/12563
Appears in Collections:机器人学研究室_期刊论文

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