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首页> 外文期刊>ISPRS International Journal of Geo-Information >Guided Image Filtering-Based Pan-Sharpening Method: A Case Study of GaoFen-2 Imagery
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Guided Image Filtering-Based Pan-Sharpening Method: A Case Study of GaoFen-2 Imagery

机译：基于导引图像滤波的平移锐化方法：以高分2图像为例

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GaoFen-2 (GF-2) is a civilian optical satellite self-developed by China equipped with both multispectral and panchromatic sensors, and is the first satellite in China with a resolution below 1 m. Because the pan-sharpening methods on GF-2 imagery have not been a focus of previous works, we propose a novel pan-sharpening method based on guided image filtering and compare the performance to state-of-the-art methods on GF-2 images. Guided image filtering was introduced to decompose and transfer the details and structures from the original panchromatic and multispectral bands. Thereafter, an adaptive model that considers the local spectral relationship was designed to properly inject spatial information back into the original spectral bands. Four pairs of GF-2 images acquired from urban, water body, cropland, and forest areas were selected for the experiments. Both quantitative and visual inspections were used for the assessment. The experimental results demonstrated that for GF-2 imagery acquired over different scenes, the proposed approach consistently achieves high spectral fidelity and enhances spatial details, thereby benefitting the potential classification procedures.
机译：高分2号（GF-2）是中国自行研制的民用光学卫星，配备了多光谱和全色传感器，是中国第一颗分辨率低于1 m的卫星。由于GF-2图像的全屏锐化方法不是以前工作的重点，因此我们提出了一种基于导引图像滤波的新型全屏锐化方法，并将其性能与GF-2的最新方法进行了比较图片。引入了引导图像滤波，以分解和传输原始全色和多光谱波段的细节和结构。此后，考虑本地光谱关系的自适应模型被设计为将空间信息正确地注入原始光谱带中。选择从城市，水体，农田和森林地区获取的四对GF-2图像进行实验。定量检查和目视检查均用于评估。实验结果表明，对于在不同场景下获取的GF-2图像，该方法始终可实现高光谱保真度并增强空间细节，从而有利于潜在的分类程序。

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