遥感图像融合的非采样Contourlet变换方法

Remotely Sensed Images Fusion Based on Non-subsampled Contourlet Transform

有效地融合高分辨率全色遥感图像(PAN)和低分辨率多光谱图像(MS),均衡融合结果中的空间细节信息和光谱信息两项特征指标,是多源遥感图像融合技术的难点。为了提高融合后图像的质量,提出了一种基于非采样Contourlet变换(NSCT)的融合方法。由于"非采样Contourlet变换"采用非采样滤波器组实现,具有移不变、高方向性和各向异性的特点,能够较好地弥补"采样的Contourlet变换(CT)"的缺陷,并且解决了小波变换方向性差的问题。实验中,以Landsat TM5图像和SPOT图像进行了算法的验证,并针对传统的直接替换、绝对值选大和局部方差选大等多分辨率融合算法与离散小波变换(DWT)及"采样的Contourlet变换"进行了对比分析,结果表明,本文方法在提高空间信息的同时,可以较好地保持原始多光谱图像中的光谱信息,弥补了"采样的Contourlet变换"在遥感图像融合应用中会导致严重的色彩畸变的缺陷。从而证明了NSCT在遥感图像融合领域是一种有效的多分辨率分解策略,可以被成功的应用到遥感图像融合应用中。

The fusion of multispectral （MS） and panchromatic （PAN） images is the nodus of Remotely Sensed Images Fusion. In order to improve the quality of the fused image, in this paper, a novel fusion strategy based on non-subsampled eontourlet transform （NSCT） is presented. Due to the non-subsampled eontourlet transform （NSCT） is obtained by coupling a non-subsampled pyramid structure with the non-subsampled directional filter bank （DFB）, and the non-subsampled contourlet transform （NSCT） is shift-invariant and high directionality, it can remedy the limitation of the subsampled contourlet （CT） transform and solve the low directional problem of discrete wavelet transform （DWT）. In the experiment we used the images of Landsat TM5 and SPOT to validate this strategy, and compared with the DWT and CT use the method of direct replace, chose the maximal absolute value and chose the maximal local Variance. The experimental results show that our method is more effective than other methods in improving the quality of image. This also proves that NSCT is an effective strategy in the field of remotely sensed images fusion, and it can be successfully used in the application of remotely sensed images fusion.