基于1αβ空间和抗混叠Contourlet变换的遥感图像融合算法

针对遥感图像中多光谱和全色图像的融合问题,提出一种基于lαβ空间和抗混叠Contourlet变换(non-aliasingcontourlet transform,NACT)的融合方法.该方法首先将多光谱图像进行lαβ变换,对其l分量和全色图像分别进行抗混叠Contourlet变换;然后,利用循环平移(cycle spinning,CS)算法消除由于变换缺乏平移不变性而引起的图像失真,对得到的低频子带系数和各带通方向子带系数分别进行融合;最后,通过抗混叠Contourlet逆变换和lαβ逆变换得到新的l分量以及融合后的高空间分辨率的多光谱图像.实验结果表明,该算法优于传统的色度-亮度-饱和度(hue-intensity-saturation,HIS)变换融合方法、小波融合方法以及Contourlet变换方法.

Fusion Algorithm for Remote Sensing Images Based on 1αβ Space and Non-aliasing Contourlet Transform

A novel image fusion algorithm based on the lap space and non-aliasing contourlet transform (NACT) is proposed for multi-spectral and panchromatic images.The multi-spectral image is first transformed into the lαβspace.The original l component and panchromatic image are decomposed into a low frequency subband image and a set of high frequency subband images by using NACT.The low frequency subband image and high frequency subband images are then fused with different fusion rules to obtain fused coefficients.Cycle spinning(CS) is introduced to reduce shift-variance of the transform. Finally,a fused multi-spectral image with high spatial resolution is generated by inverse non-aliasing contourlet transform and inverse lαβtransform.Simulation results show that the proposed method can provide better fusion pictures than the traditional hue-intensity-saturation(HIS) transform method, wavelet fusion method and contourlet transform based method.