Abstract
This paper proposed a weighted principal component analysis method based on cone response function to reserve more color information. To verify the advantages of the proposed method, Munsell spectra were used as training samples to determine the conversion model between high-dimensional spectral space and low-dimensional space, Munsell, ISO SOCS spectra and two multispectral images were used as test samples. Compared with the principal component analysis method, the proposed method can significantly improve the colorimetric accuracy at the expense of a small amount of spectral accuracy. In addition, compared with the other three weighted principal component analysis methods based on cone response function, this method has a lot of improvement in colorimetric accuracy.
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References
Cao Q, Wan X, Li J et al (2016) Updated version of an interim connection space LabPQR for spectral color reproduction: LabLab[J]. J Opt Soc Am A Opt Image, Vis 33(9):1860–1871
Taplin LA, Berns RS (2001) Spectral color reproduction based on six-color inkjet output system. In: Color and Imaging Conference
Wang Y, Zhai S, Liu J (2013) Dimensionality reduction of multi-spectral images for color reproduction [J]. J Softw 8(5):1180–1185
Maloney LT (1986) Evaluation of linear models of surface spectral reflectance with small numbers of parameters. J Opt Soc America A Opt Image Sci 3(10):1673–1683
He SH, Chen Q, Duan J (2015) The research of spectral dimension reduction method based on human visual characteristics [J]. Spectroscopy Spectral Anal 35(6):1459–1463 (in Chinese)
Shi-Wei L, Zhen L, Quan-Hui T, et al (2017) Spectral dimension reduction model research based on human visual characteristics and residual error compensation [J]. Spectroscopy Spectral Anal
University Of Eastern Finland, Spectral Color Research Group. https://www.uef.fi/spectral/spectral-databas
ISO TR (2003) 16066–2003, Graphic technology—standard object colour spectra database for colour reproduction evaluation
Yasuma F, Mitsunaga T, Iso D et al (2010) Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum[J]. IEEE Trans Image Process A Publication of the IEEE Signal Process Soc 19(9):2241–2253
Nascimento SM, Amano K, Foster DH (2016) Spatial distributions of local illumination color in natural scenes[J]. Vision Res 120:39
Imai FH, Rosen MR, Berns RS (2012) Comparative study of metrics for spectral match quality. In: Conference on colour in graphics, imaging, and vision, 2002; Society for imaging science and technology pp 492–496
Robertson AR (1977) The CIE 1976 color-difference formulae [J]. Color Res Appl 2(1)
Acknowledgments
This study is funded by Lab of Green Platemaking and Standardization for Flexographic Printing (LGPSFP-02, ZBKT201905). This work is also supported by Key Research and Development Program of Shandong Province(No. 2019GGX105016).
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Cao, Q., Li, X., Li, J. (2021). Effects of Cone Response Function on Multispectral Data Compression. In: Zhao, P., Ye, Z., Xu, M., Yang, L., Zhang, L., Zhu, R. (eds) Advances in Graphic Communication, Printing and Packaging Technology and Materials. Lecture Notes in Electrical Engineering, vol 754. Springer, Singapore. https://doi.org/10.1007/978-981-16-0503-1_14
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DOI: https://doi.org/10.1007/978-981-16-0503-1_14
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