Abstract
An efficient procedure for recovering spectral reflectance using an object’s tristimulus values under multi-illuminants is proposed by adapting with the characteristics of the testing sample to obtain the transformation matrix of pseudoinverse. Specifically, we propose the reference illuminants selection strategy and local sample weighted strategy to obtain the optimal transformation matrix under multi-illuminants condition. Selecting the reference illuminants are based on the result of the spectral angle mapper (SAM) statistics. The number of the selected local training samples and the weighted local samples can be determined by using the multicolor space Euclidean distance. To compare the experimental results, the proposed method significantly increases the spectral and colorimetric accuracy for the spectral reflectance recovery process.
Highlights
Is study proposes a more accurate recovering spectral reflectance method from tristimulus values under multiilluminants that solves the problems mentioned above
The spectral reflectance of three different dataset samples range from 400 nm to 700 nm at 10 nm intervals. e Munsell Chips were selected as the training samples in this study, and their transformation matrix was used to recover three different testing samples
We considered the Munsell Chips as the training samples to estimate the spectral reflectance of the Munsell Chips, ColorChecker SG, and Vrhel dataset under two different illuminants with the corresponding CIE 1964 XYZ tristimulus values
Summary
Is study proposes a more accurate recovering spectral reflectance method from tristimulus values under multiilluminants that solves the problems mentioned above. To obtain the matrix (AT)+ adapting with the characteristics of the testing sample, the local sample weighted strategy is proposed for calculating the spectral reflectance recovery.
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