基于改进Brovey变换的ALI影像融合算法研究

针对传统Brovey变换（Brovey Transform，BT）融合存在的光谱信息丢失及光谱扭曲等问题，引入自适应加权平均对其进行改进，并以EO-1 ALI多光谱影像为例，提出一种新的基于改进BT的多光谱影像融合算法。并分别选用信息熵、平均梯度、相关系数、均方根误差等参数对影像融合效果进行综合评价与对比分析，从而验证该算法的有效性和优越性。结果显示：采用改进后的BT融合算法的多光谱融合影像具有较好的光谱信息和空间分辨率，其视觉效果和空间纹理特征都有显著改善，并且较好地延续了源影像的色彩信息，亮度相对适中；能减少融合过程中光谱信息的损失和畸变，在保持光谱信息和清晰度方面与传统BT融合算法相比具有明显优势。

Research on ALI Image Fusion Algorithm based on Improved Brovey Transform

Aiming at the problems of spectral information loss and spectral distortion in traditional Brovey Transform (BT) fusion, the adaptive weighted average is introduced to improve it. Taking EO-1 ALI multispectral imagery as an example, a new multispectral image fusion algorithm based on improved BT is proposed. Information entropy, average gradient, correlation coefficient and root mean square error are used to comprehensively evaluate and compare the fusion effects of this algorithm, so as to verify the effectiveness and superiority of the multispectral image fusion algorithm based on improved BT. Experimental results show the multispectral fusion image using this improved algorithm has better spectral information and spatial resolution, and its visual effects and spatial texture features have been significantly improved, and the color information of the source image has been well extended, and the brightness is relatively moderate; this improved algorithm can reduce the loss and distortion of spectral information in the fusion process, and has obvious advantages in maintaining spectral information and clarity compared with the traditional BT fusion method.