光学学报, 2015, 35 (6): 0633001, 网络出版: 2015-06-02
加权视觉特性的PCA空间内光谱域映射模型
A Spectral Gamut Mapping Model in Visual Features Weighted PCA Space
视觉光学 光谱色彩管理 光谱色域映射 主成分分析法 分区最大化色域边界描述算法 visual optics spectral color management spectral gamut mapping principal component analysis segment maxima gamut bounduny descriptor algorithm
摘要
针对跨媒体光谱颜色复制过程中出现的设备光谱域不一致问题,在加权人眼视觉特性的主成分分析(PCA)光谱降维空间内构建了一种光谱域映射模型。利用标准色度观察者匹配函数构造权重系数,对高维光谱进行加权,采用PCA 提取加权光谱的前三个主元,以构造低维加权PCA 空间,在加权PCA 空间内引入分区最大化色域边界描述算法描述设备光谱域,对超设备光谱域的颜色光谱进行裁切以映射到设备光谱域内。实验证明,新模型相比于常用的PCA空间内的光谱域映射模型而言,更能达到视觉感受的匹配,可以更为有效地解决设备光谱域不一致的问题。
Abstract
In order to solve the inconsistency of device spectral gamut which happens in cross-media spectral color reproduction process, a new spectral gamut mapping model is established in visual features weighted principal component analysity (PCA) space. The standard colorimetric observer matching function is used to construct weight coefficient, which is employed to weight high dimensional spectra. Then the first three components of weighted spectra are extracted by using the PCA method, so that the low dimensional visual features weighted PCA space is set up. In the weighted PCA space, the segment maxima gamut bounduny descriptor algorithm adopted to describe the device spectral gamut, and the outside spectrum is mapped into the device spectral gamut by clipping method. The experimental result indicates that the new model can realize more visual matching than the commonly used method in PCA space, and solve the inconsistency of device spectral gamut more effectively.
刘攀, 刘真, 朱明, 吴光远. 加权视觉特性的PCA空间内光谱域映射模型[J]. 光学学报, 2015, 35(6): 0633001. Liu Pan, Liu Zhen, Zhu Ming, Wu Guangyuan. A Spectral Gamut Mapping Model in Visual Features Weighted PCA Space[J]. Acta Optica Sinica, 2015, 35(6): 0633001.