Research on the Influence of Image Linearization on Reconstruction Accuracy of Spectral Reflectance

Xiaofan Fu; Yang Xu; Changjun Li

doi:10.3788/LOP202158.1433001

[1] Hajipour A, Shams-Nateri A. Effect of classification by competitive neural network on reconstruction of reflectance spectra using principal component analysis[J]. Color Research & Application, 42, 182-188(2017).

[2] Zhang X D, Wang Q, Li J C et al. Estimating spectral reflectance from camera responses based on CIEXYZ tristimulus values under multi-illuminants[J]. Color Research & Application, 42, 68-77(2017).

[3] Zhang X D, Xu H S. Reconstructing spectral reflectance by dividing spectral space and extending the principal components in principal component analysis[J]. Journal of the Optical Society of America A, 25, 371-378(2008).

[4] Bochko V, Tsumura N, Miyake Y. Spectral color imaging system for estimating spectral reflectance of paint[J]. Journal of Imaging Science and Technology, 51, 70-78(2007).

[5] Dupont D. Study of the reconstruction of reflectance curves based on tristimulus values: comparison of methods of optimization[J]. Color Research & Application, 27, 88-99(2002).

[6] Han S, Sato I, Okabe T et al. Lecture notes in computer science[M], 323-335(2011).

[7] Harifi T, Amirshahi S H, Agahian F. Recovery of reflectance spectra from colorimetric data using principal component analysis embedded regression technique[J]. Optical Review, 15, 302-308(2008).

[8] Xiao K D, Qin Z H, Tushar C et al. Principal component analysis for skin reflectance reconstruction[C]. // Color and Imaging Conference, 22nd Color and Imaging Conference Final Program and Proceedings, November 2014,Boston, 146-150(2007).

[9] Haneishi H, Hasegawa T, Hosoi A et al. System design for accurately estimating the spectral reflectance of art paintings[J]. Applied Optics, 39, 6621-6632(2000).

[10] Xu D Y, Li X R, Zhao L Y et al. Hyperspectral remote sensing image cloud detection based on spectral analysis and dynamic fractal dimension[J]. Laser & Optoelectronics Progress, 56, 101003(2019).

[11] Shi R J, Xia F Z, Zeng W D et al. Raman spectroscopic classification of foodborne pathogenic bacteria based on PCA-Stacking model[J]. Laser & Optoelectronics Progress, 56, 043003(2019).

[12] Jin X, Zhu X Z, Li S W et al. Predicting soil available phosphorus by hyperspectral regression method based on gradient boosting decision tree[J]. Laser & Optoelectronics Progress, 56, 131102(2019).

[13] Yang P. Spectral reflectance reconstruction based on multicolor digital camera: principle and technology[M], 3(2017).

[14] Yi W J, Sun L J, Chen Z W et al. Spectral reconstruction sample analysis based on clustering analysis[J]. Packaging Engineering, 40, 249-255(2019).

[15] Liu Z H. Research on color characterization of digital camera based on polynomial regression[J]. Digital Printing, 150-156(2019).

[16] Zhao T M. Research on color space conversion algorithm based on three-dimensional look-up table method[D], 5-35(2018).

[17] Liang J X, Wan X X. Spectral reconstruction from single RGB image of trichromatic digital camera[J]. Acta Optica Sinica, 37, 0933001(2017).

[18] Amiri M M, Fairchild M D. A strategy toward spectral and colorimetric color reproduction using ordinary digital cameras[J]. Color Research & Application, 43, 675-684(2018).

[19] Hardeberg J Y. Acquisition and reproduction of colour images: colorimetric and multispectral approaches[D], 36-51(1999).

[20] Liu X X. Characterization of digital cameras based on luminance division[D], 38-40(2019).

[21] Shang M, Yang L, Liu D F et al. Emission spectral reconstruction based on principal component analysis applied to fluorescence full-color prints[J]. Nanoscience and Nanotechnology Letters, 11, 1349-1356(2019).

[22] Liang J X, Wan X X, Liu Q et al. Research on filter selection method for broadband spectral imaging system based on ancient murals[J]. Color Research & Application, 41, 585-595(2016).