Abstract: An image fusion algorithm based on wavelet transform is proposed in this paper. The image is decomposed into high-frequency image and low-frequency image. The spatial frequency and the contrast within the low-frequency image is measured to determine the fused low-frequency image. To the high-frequency image, we select these that have maximal absolute values and verify the consistency of these coefficients. The experimental results show that this algorithm can preserve all useful information from primitive images and that the clarity and contrast of the fused image are improved. The presented algorithm is verified effective for image fusion.

Key words: spatial frequency, contrast, entropy, image fusion, wavelet transform

摘要： 本文给出了一种基于小波变换的图像融合方法，对小波分解后的低频分量通过度量其图像块空间频率和对比度来确定融合图像的低频分量，对分解后得到的高频分量，选择高频系数时，基于绝对值最大的原则，并对选择结果进行一致性验证，最后重构得到融合图像。从仿真结果可以看出，文中给出的方法很好的保留了多幅原图像的有用信息，得到的融合图像清晰度和对比度都较好，是一种有效的图像融合算法。

关键词: 空间频率, 对比度, 熵, 图像融合, 小波变换