针对隐藏在衣服下的武器融合检测问题，提出了一种彩色可见光图像和红外图像融合的新算法。该算法在基于RGB、HSV和LAB彩色空间变换的基础上，使用了双树复数小波变换技术，该变换明显具有平移不变性、方向选择性、有限数据冗余性、完美重构性和较高计算效率等特点，在融合方面优于其他的小波变换。融合后的图像保持了可见光图像的高分辨率；保留了红外图像中检测出的隐藏武器；维持了可见光图像的自然色彩。该融合技术的可行性在实验中得到了验证。

A new algorithm was presented to fuse color visual image and infrared(IR) image aiming at detecting weapons hidden underneath a persons clothing. This algorithm combined dual-tree complex wavelet transform (DT-CWT) with RGB, HSV and LAB color space. DT-CWT was used due to its better properties than other wavelet transform in fusion. These properties include shift invariance, directional selectivity, limited redundancy, perfect reconstruction and computational efficiency. The fused image maintained the high resolution of the visual image, incorporated any concealed weapons detected by the IR sensor, and kept the natural color of the visual image. The feasibility of the proposed fusion technique is demonstrated by some experimental results.