基于潜在低秩表示与复合滤波的红外与弱可见光增强图像融合方法

针对传统红外与弱可见光图像融合算法中存在的亮度与对比度低、细节轮廓信息缺失、可视性差等问题,提出一种基于潜在低秩表示与复合滤波的红外与弱可见光增强图像融合方法.该方法首先利用改进的高动态范围压缩增强方法增强可见光图像提高亮度;然后利用基于潜在低秩表示与复合滤波的分解方法分别对红外与增强后的弱可见光图像进行分解,得到相应的低频和高频层;再分别使用改进的对比度增强视觉显著图融合方法与改进的加权最小二乘优化融合方法对得到的低频和高频层进行融合;最后将得到的低频和高频融合层进行线性叠加得到最终的融合图像.与其他方法的对比实验结果表明,用该方法得到的融合图像细节信息丰富,清晰度高,具有良好的可视性.

Infrared and Low-light-level Visible Light Enhancement Image Fusion Method Based on Latent Low-rank Representation and Composite Filtering

Due to the problems of low brightness and contrast,lack of detail contour information and poor visibility in the traditional infrared and low-light visible image fusion algorithm,an infrared and low-light visible enhancement image fusion method based on potential low-rank representation and composite filtering is proposed.Firstly,the improved high-dynamic-range compression enhancement method is used to enhance the brightness of low-light visible images.Secondly,the infrared and enhanced low-light visible images are respectively decomposed by using a decomposition method based on latent low-rank representation and composite filtering,and the corresponding low-frequency and high-frequency layers are obtained.Then,the improved contrast-enhanced visual-saliency-map fusion method and improved weighted least squares optimization fusion method are used to fuse the obtained low-frequency and high-frequency layers respectively.Finally,the low-frequency and high-frequency fusion layers are linearly superposed to obtain the final fusion image.Compared with other methods,the experimental results show that the fused image obtained by the proposed method has abundant detail information,high clarity and good visibility.