摘要
针对光谱色彩管理中光谱空间维度高引起多光谱图像处理时间长、所需存储空间大的问题,提出构造中间空间的方法。首先通过分析色彩管理过程,引入中间空间,建立以中间空间为设备无关颜色空间的光谱色彩管理流程;然后针对多光谱图像的打印输出,采用主成分分析法对打印机特征化光谱样本进行降维,将降维后的特征空间作为中间空间;最后采用特征向量矩阵实现任意多光谱图像数据到中间空间的变换。实验表明,采用打印机特征化光谱样本生成的中间空间与光谱空间的变换效率高,变换的光谱和色度精度高,图像数据降维后能保持源图像光谱的主要信息。
High dimension of the spectral space in spectral color management results in long run time and large memory requirement in color processing of multi spectral images. To overcome this shortcoming,a method to construct intermediate space was proposed. 13y analyzing the color management process, an intermediate space was introduced and the flow of spectral color management based on the intermediate space was established firstly. Then for the printing applicalion of multi-spectral images, the principal component analysis method was employed to construct an eigenvector space based on the printer characteristic samples. The new space derived from the method was appointed as the intermediate space. Finally the eigcnvector matrix was utilized to achieve the transformation between the intermediate space and the spectral space. Experiments show that the transformation efficiency is increased when the printer characteristic samples are used during dimension reduction. The colorimetric and spectral precision of the conversion is high and low-dimensional image data in the intermediate space can keep the main information of the source spectral data.
出处
《计算机科学》
CSCD
北大核心
2010年第5期247-250,共4页
Computer Science
基金
国家部委"十一五"预研项目(No.51316060203)
国家部委预研基金项目(No.9140A16050109DZ01)资助
关键词
光谱色彩管理
中间空间
主成分分析
多光谱图像
tral color management Intermediate space Principal component analysis Multi spectral image
