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Sequential adaptive estimation for spectral reflectance based on camera responses
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DOI：10.1364/OE.389614.png)
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A sequential weighted nonlinear regression technique from digital camera responses is proposed for spectral reflectance estimation. The method consists of two stages taking colorimetric and spectral errors between training set and target set into accounts successively. Based on polynomial expansion model, local optimal training samples are adaptively employed to recover spectral reflectance as accurately as possible. The performance of the method is compared with several existing methods in the cases of simulated camera responses under three kinds of noise levels and practical camera responses under the self as well as cross test conditions. Results show that the proposed method is able to recover spectral reflectance with a higher accuracy than other methods considered. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Keyword:
WIENER ESTIMATION
RECONSTRUCTION
KERNEL
RECOVERY
SET
期刊
IF:
3.3
论文数:
6.1W
被引数:
14.3W
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分享收藏分享收藏Spectra estimation from raw camera responses based on adaptive local-weighted linear regression.png)
OPTICS EXPRESSOAAI
OPTICS EXPRESSIF3.3
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