基于能量分割的空间域图像融合算法研究

Research on Spatial Domain Image Fusion Algorithm Based on Energy Segmentation

针对空间域图像融合存在不同图源差异性信息提取、融合权重选取困难等问题,提出了一种新的空间域图像融合算法。利用矩阵相似的基本原理,对红外图像矩阵进行对角化变换,计算可见光图像矩阵在主要特征向量上的映射,采用加权融合的方法处理特征值矩阵,对融合矩阵进行对角化逆变换重构融合图像。实验结果表明,算法在充分保留源图像有效信息的同时,融合图像的整体灰度得到了明显的改善,具有良好的图像质量评估指数和更加优秀的视觉效果。

To address the problems of image fusion in the spatial domain, such as the extraction of different image sources, and challenges in selecting fusion weights, a new spatial-domain image-fusion algorithm is proposed. Using the basic principle of matrix similarity, the infrared image matrix is diagonally transformed and the visible light image matrix is mapped onto the main eigenvectors. Then, the weighted fusion method is used to process the eigenvalue matrix and the fusion matrix is diagonalized as an inverse-transformed and reconstructed fusion image. The experimental results show that the algorithm fully retains the effective information of the source image;moreover, the overall grayscale of the fused image is significantly improved.Thus, the algorithm offers a strong image quality evaluation index and better visual effects.