The fusion of infrared and visible images has been playing an important role in various scenarios all over the world. For the fusion results from most of the existing techniques in this area, some features, such as the image contrast and edge details, are still needed to be improved. In this Letter, a new fusion method of the infrared and visible image is rendered. In this method, the infrared image is preprocessed to improve the contrast. Then, the two source images are decomposed based on non-subsampled shearlet transform (NSST). The fusion rules based on regional energy and co-occurrence filtering are proposed for the low-frequency and high-frequency NSST coefficients, respectively. Experimental results show that the proposed method can effectively retain the details of the source image, meanwhile improve the contrast of the fused image.

中文翻译：

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基于非下采样剪切波变换、区域能量和共生滤波的红外与可见光图像融合

红外和可见光图像的融合在世界各地的各种场景中都发挥着重要作用。对于该领域大多数现有技术的融合结果，图像对比度和边缘细节等一些特征仍有待改进。在这封信中，提出了一种新的红外和可见光图像融合方法。在该方法中，对红外图像进行预处理以提高对比度。然后，基于非下采样剪切波变换（NSST）对两个源图像进行分解。分别针对低频和高频NSST系数提出了基于区域能量和共生滤波的融合规则。实验结果表明，该方法能有效保留源图像的细节，同时提高融合图像的对比度。