目的 针对跨媒体光谱颜色复制中不同颜色媒介光谱色域不一致的问题，在LMS-PCA光谱空间下构建一种修改LMS加权特性的PCA空间内光谱色域映射模型。方法 利用调整后的修改LMS加权函数对高维光谱数据进行加权，采用主成分分析法提取其加权光谱的前3个主成分，用以构建LMS-PCA光谱链接空间。在LMS-PCA空间内引入分区成熟SMGBD算法描述设备的光谱色域，对超出设备光谱色域的图像颜色点进行LSLINceLmax色域压缩以映射到设备光谱域内，LSLINceLmax色域压缩基于传统LSLIN算法优化得到。结果 新模型相比于利用其他色域映射方向的光谱色域映射模型，以及普通加权视觉特性的PCA空间内光谱域映射模型，拥有更高的光谱精度和色度精度，且在变观察环境下具有稳定的色差精度。结论 修改LMS加权特性的PCA空间内色域映射模型能够基本解决变观察环境下，不同颜色媒介光谱色域不一致的问题，具有较好的实用性。

The work aims to establish a spectral gamut mapping model in the modified LMS weighted PCA space with respect to the spectral gamut inconsistency of media in different colors in cross-media spectral color reproduction process. The high-dimensional spectral data was weighted by the modified LMS weighted function after adjustment. Then, the first three principal components of weighted spectra were extracted by using the principal component analysis (PCA) method, so that the LMS-PCA spectral link space was set up. In the LMS-PCA space, the mature segment maxima gamut boundary descriptor (SMGBD) algorithm was adopted to describe the device spectral gamut, and the image color points outside the device spectral gamut were subject to LSLINceLmax gamut compression and then mapped into the device spectral field. LSLINceLmax gamut compression was achieved based on the optimization of traditional LSLIN algorithm. The new model had higher spectral accuracy and chromaticity accuracy than the spectral gamut mapping models using other gamut mapping directions and the spectral gamut mapping model in ordinary visually-featured weighted PCA space. Moreover, it had stable color difference accuracy under changing observation environment. The gamut mapping model in the modified LMS weighted PCA space can basically solve the spectral gamut inconsistency of media in different colors under changing observation environment and it has agreeable practicality.