摘要
针对红外与可见光图像所表现的目标特征不同,提出了一种基于IHS和小波变换的图像融合方法.首先对可见光图像进行IHS变换得到亮度I、色度H、饱和度S 3个分量,再对红外图像进行灰度变换;然后对亮度分量和已变换红外图像进行小波分解,对低频分量和高频分量分别采用不同的融合规则;最后进行IHS逆变换得到融合图像.实验结果表明,该方法在红外与可见光图像融合处理中取得了很好的融合效果,优于传统的IHS变换法和小波变换方法.该方法保留了可见光图像高的空间分辨率和丰富的纹理细节信息,同时融合了在可见光图像中看不到而在红外图像里可以观察到的热目标.
The infrared and visual images show different features for the same object,and considering these features this paper proposes an image fusion method based on IHS and wavelet transform.Firstly,the visual image is transformed by the IHS transform,and intensity(I),hue(H),saturation(S) components are obtained,and the infrared image is transformed by gray transform.Secondly,the intensity component and transformed infrared image are decomposed respectively by wavelet transform,different fusion rules are applied to coefficients of low frequency and high frequency.Finally,we could obtain the final fused image by IHS inverse transform.The experimental data shows the image fusion method is effective for the fusion of infrared and visual images and the fused image outperforms the traditional IHS transform method and the traditional IHS combining wavelet transform method.The proposed method can keep a high spatial resolution and rich texture detail information of visual image,and at the same time fuse the heat target that cannot be seen in the visible image while can be observed in the infrared image.
出处
《智能系统学报》
北大核心
2012年第6期554-559,共6页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金资助项目(61201238)