Paper
4 February 2013 Estimation of reflectance based on properties of selective spectrum with adaptive Wiener estimation
Author Affiliations +
Proceedings Volume 8652, Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications; 86520D (2013) https://doi.org/10.1117/12.2005444
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
To accurately represent the colors in a real scene, a multi-channel camera system is necessary. One of the applications of the data acquired with the multi-channel camera system is the spectral reflectance estimation. One of the most widely used methods to estimate the spectral reflectance is the Wiener estimation. While simple and accurate in controlled conditions, the Wiener estimation does not perform as well with real scene data. Therefore, the adaptive Wiener estimation has been proposed to improve the performance of the Wiener estimation. The adaptive Wiener estimation uses a similar training set that was adaptively constructed from the standard training set according to the camera responses. In this paper, a new way of constructing such similar training set using the correlation between each spectral reflectance in the standard training set and the first approximation of the spectral reflectance that was obtained by the Wiener estimation is proposed. The experimental results showed that the proposed method is more accurate than the conventional Wiener estimations.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ji-Hoon Yoo, Wang-Jun Kyung, Ho-Gun Ha, and Yeong-Ho Ha "Estimation of reflectance based on properties of selective spectrum with adaptive Wiener estimation", Proc. SPIE 8652, Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications, 86520D (4 February 2013); https://doi.org/10.1117/12.2005444
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Cited by 4 scholarly publications.
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KEYWORDS
Reflectivity

Cameras

Imaging systems

Error analysis

Optical filters

Data acquisition

Sensors

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