基于独立成分分析和IHS变换域的灰度可见光和红外图像融合

针对灰度可见光和红外图像的融合图像缺乏色彩信息、图像的高阶信息在变换域中统计独立性不足的缺陷, 提出一种基于独立分量分析和IHS (亮度-色度-饱和度) 变换域的融合方法. 该方法利用IHS 变换域能够有效分离图像亮度分量和彩色信息的优势, 对灰度可见光图像建立灰度图像的彩色传递模型. 利用各分量的独立性进行基于独立分量分析和IHS 变换域的图像融合, 并得到最终的彩色融合图像, 使融合图像更加符合人类视觉要求. 仿真实验验证了所提出算法的有效性.

Fusion technique for grey-scale visible light and infrared images based on independent component analysis and intensity-hue-saturation transform

The image fusion based on gray-scale visible light and infrared images lacks color information. Meanwhile, the independency of images’ high-order information is insufficient in transform domain statistics. Therefore, an image fusion approach based on independent component analysis and IHS transform space is presented. The IHS transform can separate the image intensity component and color information effectively. Firstly, the color transfer model of gray-scale image for gray-scale visible light images is erected by IHS transform. Then, according to each component’s independency, the images are fused based on ICA and IHS transform. The final color fused image is got, which fits the need of human vision better. Experimental results validate the effectiveness of the proposed method.