• Acta Optica Sinica
  • Vol. 36, Issue 3, 333001 (2016)
He Songhua1、*, Gao Yuan1, Chen Qiao1, and Duan Jiang2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    DOI: 10.3788/aos201636.0333001 Cite this Article Set citation alerts
    He Songhua, Gao Yuan, Chen Qiao, Duan Jiang. The Set up of Primary Pigments Liner Mixing Space in Spectral Color Reproduction[J]. Acta Optica Sinica, 2016, 36(3): 333001 Copy Citation Text show less
    References

    [1] He Songhua, Liu Zhen, Chen Qiao. The research of spectral dimension reduction method based on the matrix thoery[J]. Acta Optica Sinica, 2014, 34(2): 0233001.

    [2] Xu Xiangyang, Chen Guangxue. Research of visual distance blur algorithm based on multi-scale overlay[J].Acta Optica Sinica, 2014, 34(2): 0233002.

    [3] Tzeng D. Spectral-Based Color Separation Algorithm Development For Multiple-Ink Color Reproduction[D]. Rochester: Rochester Institute of Technology, 1999: 66-108.

    [4] Li Jincheng, Liu Zhen, Chen Guangxue, et al.. Colorant selection based on gamut analysis and cluster analysis[J]. Acta Optica Sinica, 2009, 32(6): 0633001.

    [5] Liu Pan, Liu Zhen, Zhu Ming, et al.. A spectral gamut mapping model in visual features weighted PCA space[J]. Acta Optica Sinica, 2015, 35(6): 0633001.

    [6] Xu Faqiang, Wan Xiaoxia, Zhu Yuanhong. Color component prediction based on rotated principal component analysis[J]. Optics and Precision Engineering, 2008, 16(3): 518-523.

    [7] He Songhua, Chen Qiao, Duan Jiang. The research of spectral dimension reduction method based on human visual characteristics[J]. Spectroscopy and Spectral Analysis, 2015, 35(6): 1459-1463.

    [8] Wang Y, Zeng P, Luo X, et al.. Low- dimensional multi- spectral space for color reproduction based on nonnegative constrained principal component analysis[J]. Journal of Southeast University, 2009, 2(4): 486-490.

    [9] Paatero P, Tapper U. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values[J]. Environmetrics, 1994, 5(2): 111-126.

    [10] He S, Liu Z. The linear colorant mixing space based on Kubleka-Munk turbid media theory[J]. Procedia Engineering, 2011, 23: 320-325.

    [11] Zong Chunli. The Dimension Reduction for High-Dimensional Multispectral Space[D]. Xi’an: Xidian University, 2010: 39- 42.

    [12] Zhao Y. Image Segmentation and Pigment Mapping of Cultural Heritage Based on Spectral Imaging[D]. Rochester: Rochester Institute of Technology, 2008: 130-165.

    [13] Urban P, Rosen M P, Berns R S. Accelerating spectral-based color separation within the Neugebauer subspace[J]. Journal of Electronic Imaging, 2007, 16(4): 043014.

    [14] Tzeng D Y, Berns R S. Spectral-based ink selection for multiple-ink printing I: Colorant estimation of original object[C]. Color and Imaging Conference, 1998: 106-111.

    He Songhua, Gao Yuan, Chen Qiao, Duan Jiang. The Set up of Primary Pigments Liner Mixing Space in Spectral Color Reproduction[J]. Acta Optica Sinica, 2016, 36(3): 333001
    Download Citation