摘要
遥感数据融合是多源遥感海量数据富集表示的有效途径。如何在提高融合影像空间分辨率的同时最大限度地保持光谱信息是长期以来遥感数据融合研究的焦点内容。本文以ALOS PRISM和ALOS AVNIR-2传感器的数据为数据源,比较研究了遥感领域中常用和代表性的BROVEY、IHS、MULTIPLICATIVE、PCA、WAVELET和HPF六种融合方法,并通过主观评价和定量分析对融合效果进行了综合评价。实验结果表明,HPF方法在显著提高融合影像空间分辨率的同时,有效保持了多光谱影像的光谱信息,是适合ALOS数据的最优融合方法。
Image fusion is the technique to integrate disparate and complementary information of multi-source imagery to enhance the information apparent in the images as well as to increase the reliability of the interpretation. How to keep the spectral information while improving the spatial resolution during the fusion process has always been the research focus. This paper selected the most commonly used and the most predominant image fusion methods, including Brovey, IHS transformation, Multiplicative, PCA, Wavelet and HPF, for the fusion of the data from ALOS PRISM sensor and data from ALOS AVNIR-2 sensor. It comprehensively evaluated the performance of each method by qualitative and quantitative comparison and analysis. Research results indicate that HPF is the most effective method for the fusion of ALOS data; while it greatly improves the spatial resolution, the spectral information is preserved to the maximum extent.
出处
《测绘科学》
CSCD
北大核心
2008年第6期121-124,共4页
Science of Surveying and Mapping
关键词
遥感
ALOS
影像融合
定量评价
remote sensing
ALOS
image fusion
quantitative assessment
