基于边缘和对比度的小波变换图像融合算法

Wavelet Transform Image Fusion Algorithm Based on Edge and Contrast

针对传统融合算法在图像融合时,不能很好地保留源图像信息和边缘信息的缺点,提出了一种基于边缘和对比度的加权图像融合算法。该算法利用小波变换对图像进行分解,分解后分别得到图像的低频系数和高频系数,对高频系数采用高频融合规则;对低频系数采用低频融合规则;最后通过小波逆变换得到融合图像。实验结果表明,该改进的融合算法与传统融合算法相比,融合效果更好,生成的融合图像具有边缘信息丰富、图像清晰度高等优点。

In the traditional fusion algorithm in image fusion,the source image and edge information can not be preserved well,this paper proposes a weighted fusion algorithm based on image edge and contrast. The algorithm decomposes the image by wavelet transform,and obtains the low frequency coefficient and the high frequency coefficient of the image after the decomposition. The high-frequency fusion rule is adopted for the high frequency coefficient,and the low frequency fusion rule is adopted for the low frequency coefficient. Finally,the fused image is obtained through inverse wavelet transform. The experimental results show that the improved fusion algorithm has better fusion effect compared with the traditional fusion algorithm,and the generated fusion image has the advantages of rich edge information and high image clarity.