基于双变换的红外与可见光图像融合增强

通过研究可见光视觉图像与红外图像序列的相关特性及融合处理中存在的问题, 提出一种基于视觉图像预增强处理的曲波与小波双变换融合机制来有效保留边缘信息和图像细节信息。实验结果表明所提出的方法提高了融合图像的视觉感知质量, 为遮挡和伪装目标的检测和定位提供了更为有效的空间环境, 并且融合增强后的图像具有更高的信噪比和更少的人工痕迹, 与当前最新的其他方法相比是一种具有更好融合质量和更高效率的图像/视频融合方法。

Infrared and visual image fusion enhancement by dual-transform

This paper proposed a novel method by studying the characteristics of visual, infrared image/video and the problems introduced from the fusion processing. The proposed method enhanced the illumination of the visual image firstly, and then used curvelet and wavelet dual-transform to save the edge information and preserve the details of the visual and the infrared images during the fusion enhancement. Experimental results show that the proposed method enhances human perception for image/video and improves camouflaged target's detection and location in complex environment. It is proved to be a high quality and high efficiency image/video fusion method with the characters of higher PSNR and less artifact compared with the other state-of-the-art methods.