| Project/Area Number |
17500131
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Kinki University |
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Principal Investigator |
SHIMANO Noriyuki Kinki University, School of Science and Engineering, Professor (10257975)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,150,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥150,000)
Fiscal Year 2007: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2006: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2005: ¥700,000 (Direct Cost: ¥700,000)
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| Keywords | image acquisition / noise / recovery of spectral reflectance / evaluation of a set of sensors / Wiener estimation / multispectral camera / 分光反射率復元 / 最適化 / 画像取得 |
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| Research Abstract |
Digital archive of art paintings and objects is a key technology to record and to leave them as historical heritages for the future. Since the impressions of a painting change extremely by the changes in the illuminations, the reproduction of a color image under a variety of illuminations by taking account of the chromatic adaptation of the visual system is very important. Therefore, the accurate recovery of spectral reflectances of the imaged objects through the use of image data is very important for the purpose
In this project, we developed a model to estimate the noise variance of an image acquisition system by using the spectral reflectances of the learning color samples and their corresponding image data, and applied it to recover spectral reflectances by the Wiener estimation without prior knowledge of the spectral reflectances of the imaged objects. The accuracy of the recovered spectral reflectances by this proposal was compared with other recovery models and it is confirmed that the results by this proposal is the most accurate when test samples are different from learning samples. We also developed a model for the evaluation of a set of sensors aimed at the acquisition of colorimetric information and spectral information, and applied the model to develop the optimal seven channel spectral sensitivities of a multispectral camera.
Finally, the spectral reflectances of the several art paintings were recovered by using the multispectral camera, and then color images were reproduced under a variety of illuminations
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