基于归一化相关矩的多分辨率遥感图象融合

多传感器数据融合技术已广泛应用于遥感图象处理方面 .针对遥感多光谱图象空间分辨率较低的问题 ,提出了一种基于归一化相关矩的多分辨率图象融合方法 .该方法首先对图象进行二维小波变换 ,然后根据所得到的高频小波系数的一阶、二阶统计特征来定义图象局部灰度相关矩 ,并以此作为图象融合测度来对遥感图象进行多分辨率特征融合 ,从而得到包含更多信息和有效特征的融合图象 .仿真结果表明 ,融合后的图象在保留多光谱信息和提高空间分辨率上均能获得较好的效果 ,因而可以更好地用于目标识别、分类等遥感图象处理方面

Multiresolution Remote Sensing Image Fusion Based on the Normalized Correlation Moment

Multisensor data fusion technique has been widely used in remote sensing image processing. A major problem in using remote sensing multispectral images is the low spatial resolution. In order to improve spatial resolution of the multispectral images, a multiresolution image fusion method based on the normalized correlation moment is proposed in this paper. After 2 D wavelet transform the normalized correlation moment is defined by means of statistic first order and second order moment of those wavelet coefficients with high frequency component under different resolutions. By using the local correlation moment as measure of feature selection, the new method carries out multiresolution images fusion. And the fused images include more useful information for further application. Experiments are conducted on Landsat TM and SPOT data. Computer simulations show that the fused images obtain better results in terms of both preserving spectral information and improving spatial resolution of the multispectral images, and are rather used to many aspects of remote sensing image processing such as target recognition, ground materials classification, etc.