基于四元数奇异值分解的数字印刷质量评价

目的针对人眼视觉感受与印刷质量评价结果存在不一致的缺陷,提出全四元数及奇异值分解的数字印刷质量评价方法。方法首先,依据图像颜色空间属性,采用四元数作为印刷图像表示模型,其中四元数矩阵实部为图像亮度方差,虚部为红、绿、蓝颜色,建立印刷图像全四元数表示模型。然后,对四元数图像模型进行四元数奇异值分解,得到图像四元数特征向量。最后,印刷图像质量评价指标以图像奇异值特征向量线性相关程度进行衡量。结果印刷图像四元数模型可完整地表示数字印刷图像,有效地凸显人眼视觉敏感结构信息,在印刷质量评价中实现了图像信息并行处理。结论印刷图像四元数模型提高和改善了彩色印刷图像质量准确性,与人眼视觉特性一致性较好。

Digital Printing Quality Assessment Based on Quaternion Singular Value Decomposition

The work aims to propose digital printing quality assessment method based on quaternion singular value decomposition for the defect of the human visual perception not conforming to the result of printing quality assessment. First of all, according to the color characteristics of printing images, quaternion was adopted as a printing image representation model. The real part of the quaternion matrix was the image brightness variance, and the imaginary part was red, green and blue. Thus, a full quaternion representation model of printing images was established. Singular value decomposition was carried out to the full quaternion matrix to obtain the singular value vector of the quaternion matrix corresponding to blocks. Finally, the printing image quality assessment index was measured by the linear correlation degree of image singular value feature vector. Quaternion model of printing images could completely represent digital printing images, effectively highlight sensitive structural information of human vision, and realize parallel processing of image information in printing quality assessment. Quaternion model of printing image improves and increases the accuracy of color printing image quality and has good consistency with human visual characteristics.