为了提高融合图像质量评价中评价结果与人眼视觉特性的一致性, 分析了现有融合图像质量评价方法, 提出了一种基于图像结构信息复数表示的融合图像质量评价方法, 通过计算图像亮度分量的梯度, 构成了一种表征图像结构信息的梯度复数矩阵, 用该矩阵表征图像的结构信息。考虑到复数无法计算互信息等参数, 将分块奇异值分解后得到的矩阵作为度量矩阵, 采用该矩阵计算了两种融合图像质量评价方法。实验结果表明, 该方法提高了评价结果与人眼视觉特性的一致性, 对于融合效果较好的金字塔和小波方法给出了3748 5和3722 2的评价结果, 与人眼视觉特性的一致性优于传统方法。

In order to improve the consistency of the assessment result of image fusion with that of Human Visual System, the state-of-the-art image fusion assessment methods are deeply analysed, then a new assessment method is proposed in this paper, which is based on the complex number expression for image structure. The gradient information of luminance layer of color image is used to perform the task. When it is used to describe image structure, more human visual system-sensitive information are contain in the corresponding complex matrix. Due to the calculation problem of mutual information, we perform singular value decomposition on the complex matrix, and the singular value vector of each image block is used to construct the new matrix. Results from experiments show that the proposed method gives evaluation of 3748 5 and 3722 2 for pyramid and DWT methods. It improves the consistency of assessment results with those of human visual system.