基于Contourlet变换和广义高斯参数估计的遥感图像融合

Pansharpening with CT and Generalized Gaussian Distribution

为了降低多光谱图像与全色图像融合过程中的光谱扭曲和空间失真,提出了一种基于Contourlet变换和广义高斯分布的遥感图像融合方法。首先将多光谱图像和全色图像经过Contourlet变换后得到它们的低频信息和高频信息,对低频信息采用加权平均的融合规则、对高频信息采用广义高斯参数估计的方法进行融合,最后将融合的低频信息和高频信息进行逆变换,得到融合后的高分辨多光谱图像。将文中方法应用于Geoeye_1卫星数据,与同类方法的对比分析结果显示:该方法能够减少光谱扭曲和空间信息的损失,得到的融合结果在视觉效果和客观评价标上均优于对比方法。

In order to reduce the spectral and spatial distortions, a novel method based on CT and Generalized Gaussian Distribution is proposed for multispectral and panchromatic images fusion. First, the low-frequency information and high-frequency information is obtained through CT transformation. The low-frequency is fused by the rule of weighted average, and the high-frequency is fused in accordance with the rule of Generalized Gaussian Distribution. Thus, the high spatial resolution multispectral image is produced through the inverse of CT transformation. Some experiments are taken on Geoeye_1 satellite datasets, and the experimental results show that our proposed method can reduce distortions in both the spectral and spatial domains, and outperform some related Pan-Sharpening approaches in visual results and numerical guidelines.