Abstract: A fusion method for multi-band remote sensing images based on Curvelet transform is proposed. The Curvelet transform represents edges better than wavelets, and is therefore well-suited for image fusion. The multi-
band remote sensing images are decomposed using Curvelet transform, which have multi-scale, multi-direction characteristics. For the low-pass coefficients, an averaging fusion rule is used. According to edge distribution differences in high frequency sub-band images, for the directional high-frequency coefficients, region edge detection and region spectrum entropy algorithm are used to select the better coefficients for fusion. Experimental results show that compared with traditional algorithm, the proposed algorithm can get better visual effect and the significant information of original image like textures and contour details is well maintained.

Key words: Curvelet transform, multi-band remote sensing image, spectrum entropy, image fusion

摘要： 提出一种基于Curvelet变换的多波段遥感图像融合算法。Curvelet变换具有比小波变换更好的边缘表达，因而更适合图像的融合处理。采用具有多尺度、多方向特点的Curvelet变换对多波段遥感图像像进行分解。对于低频系数采用平均融合算法，根据高频子图边缘分布差异，对于方向高频系数采用区域边缘检测和区域谱熵算法实现多波段遥感图像的融合处理。实验结果表明，提出的算法与传统算法相比在保留原始图像边缘和纹理信息同时，可以有效地取得较好的融合视觉效果。

关键词: Curvelet变换, 多波段遥感图像, 谱熵, 图像融合