Recovering sensor spectral sensitivity from raw data

Denglu Wu; Jiandong Tian; Bingfeng Li; Yaonan Wang; Yandong Tang

doi:10.1117/1.JEI.22.2.023032

21 June 2013 Recovering sensor spectral sensitivity from raw data

Denglu Wu, Jiandong Tian, Bingfeng Li, Yaonan Wang, Yandong Tang

Author Affiliations +

Journal of Electronic Imaging, Vol. 22, Issue 2, 023032 (June 2013). https://doi.org/10.1117/1.JEI.22.2.023032

Abstract

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.

Citation Download Citation

Denglu Wu, Jiandong Tian, Bingfeng Li, Yaonan Wang, and Yandong Tang "Recovering sensor spectral sensitivity from raw data," Journal of Electronic Imaging 22(2), 023032 (21 June 2013). https://doi.org/10.1117/1.JEI.22.2.023032

Published: 21 June 2013

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