Abstract
An ideal fusion method preserves the Spectral information in fused image and adds spatial information to it with no spectral distortion. Among the existing fusion algorithms, the contourlet-based fusion method is the most frequently discussed one in recent publications, because the contourlet has the ability to capture and link the point of discontinuities to form a linear structure. The Brovey is a popular pan-sharpening method owing to its efficiency and high spatial resolution. This method can be explained by mathematical model of optical remote sensing sensors. This study presents a new fusion approach that integrates the advantages of both the Brovey and the cotourlet techniques to reduce the color distortion of fusion results. Visual and statistical analyzes show that the proposed algorithm clearly improves the merging quality in terms of: correlation coefficient, ERGAS, UIQI, and Q4; compared to fusion methods including IHS, PCA, Adaptive IHS, and Improved Adaptive PCA.
Abstract (translated)
理想的融合方法保留了融合图像中的光谱信息，并为其添加了空间信息，没有光谱失真。在现有的融合算法中，基于轮廓波的融合方法是最近出版物中最常讨论的融合方法，因为轮廓波具有捕获和链接不连续点以形成线性结构的能力。由于其效率和高空间分辨率，Brovey是一种流行的全锐化方法。该方法可以通过光学遥感传感器的数学模型来解释。本研究提出了一种新的融合方法，它结合了Brovey和cotourlet技术的优点，以减少融合结果的颜色失真。视觉和统计分析表明，该算法在以下方面明显提高了合并质量：相关系数，ERGAS，UIQI和Q4;与融合方法相比，包括IHS，PCA，自适应IHS和改进的自适应PCA。
URL
https://arxiv.org/abs/1807.09610
