改进的基于小波变换的图像融合技术

An Improved Image Fusion Method Based on a Wavelet Transform

图像融合旨在构建更适合人类和机器感知的图像.在遥感应用中,高分辨率全色(PAN)图像和低分辨率多光谱(MS)图像的融合一直是一个问题,并引起了广泛关注.本文提出了一种基于小波变换的PAN和MS图像融合算法.在两个图像上执行小波变换后,使用边缘强度因子(EIF)将PAN图像的低频成分融合到MS图像的低频成分中.然后,基于最大局部标准偏差标准(MLSTD)对图像的高频成分进行融合以获得高频特征.最后,通过小波逆变换,从融合后的低频和高频分量中获得高分辨率和多光谱的融合图像.实例说明融合图像很好地配备了所需的特征,并且所提出的算法比几种经典方法具有更好的性能.

Image fusion aims to construct images that are more appropriate and understandable for human and machine perception. In remote sensing applications, the fusion of the high-resolution panchromatic(PAN) image and the low-resolution multi-spectral(MS) image has always been a problem and has drawn much attention. In this paper,we propose a PAN and MS image fusion algorithm based on a wavelet transform. Firstly, after performing a wavelet transform on both images, the PAN image’s low-frequency components are fused into the MS image’s low-frequency components by using the edge intensity factor(EIF). Then, the high-frequency components of images are fused to obtain high-frequency features based on the maximum local standard deviation criterion(MLSTD). Finally, the high-resolution and multi-spectral fused images can be obtained by the wavelet inverse transform from the fused low-frequency and high-frequency components. Examples illustrate that the fused images are well equipped with desired features, and the proposed algorithm performs better than several classical methods.