基于块方向性小波变换的图像融合算法

Image fusion algorithm based on patch-based directional wavelets

针对传统小波变换存在的缺陷,提出了一种基于块方向性小波变换的图像融合算法.将输入的图像均匀划分成多个子块,并通过训练确定每块图像的方向性小波;利用块方向性小波对图像进行稀疏变换得到稀疏系数,对融合系数进行逆变换得到融合图像,并采用仿真实验对算法性能进行测试。实验结果表明,相对于其它图像融合算法,如DTC、FFT和DWT等,本算法无论是在近物图像、遥感图像还是红外线图像上,其信息熵和平均梯度等图像融合质量评价指标都更优,使图像融合过渡效果更加自然。同时其图像融合速度更快,可以满足图像处理系统实时性的需求。

In order to solve defect of the traditional wavelet transform, a novel image fusion algorithm based on patch-based directional wavelet was proposed. The image was divided into many patches, and the directional wavelet was obtained by training each patch, and then the sparse coefficients of input images were acquired by sparsely represented using the directional wavelet. The fused image was reconstructed by transforming the coefficients reversely, and the simulation experiment was used to test performance of the algorithm. The experimental results show that the proposed algorithm makes the image fusion transition effect more natural compared with the traditional algorithm such as DTC, FFT and DWT. Because it＇s image fusion quality evaluation indexes are better in the information entropy and the average gradient. At the same time, the image fusion is faster and it can meet the demand of real-time image processing system.