联合IHS 变换和MAP 估计的遥感图像融合

为了提高多光谱图像和全色图像的融合质量, 提出一种基于推广的IHS(Generalized Intensity-Hue-Saturation, GIHS)变换与最大后验概率MAP(Maximum a Posteriori)相结合的遥感图像融合算法。该算法首先经过GIHS 变换, 由多光谱图像得到强度分量; 其次针对强度分量和全色图像, 通过MAP 构建高分辨率图像的成像模型, 采用最速下 降优化算法得到富含光谱信息的高分辨率全色图像; 进而依据GIHS 变换得到融合图像。实验中分别以IKONOS 卫 星、Quickbird 卫星的多光谱图像和全色图像为例, 进行融合算法验证, 并与GIHS 融合算法、传统的小波变换融合 算法、小波变换结合IHS 变换的融合算法等进行比较分析, 实验表明, 新的融合方法具有更好的融合效果。

Remotely-sensed image fusion based on generalized IHS\ntransformation and MAP analysis

This paper proposes a fusion method by combining generalized intensity-hue-saturation (GIHS) transformation and maximum a posteriori (MAP) analysis in order to improve the fusion quality of multispectral (MS) and panchromatic (Pan) images from a new type of remote sensing platforms. The intensity component of the MS images is first obtained by GIHS transformation. Then a new Pan image is acquired by combing the intensity component and Pan image using a steepest-descent optimization algorithm based on the MAP framework. Thus, the fused images are obtained by the GIHS method. Experiments are conducted using the IKONOS MS and Pan images, and Quickbird MS and Pan images. The proposed method is compared with the GIHS fusion method, the wavelet transform (WT) fusion method, and the combined WT-GIHS fusion method. The experimental results show that the proposed method can achieve better fusion result than exiting fusion methods.