Remote sensing image data object level space-time fusion method

Abstract

The invention discloses a remote sensing image data object-level space-time fusion method, which comprises the following steps of: acquiring a first remote sensing image and a second remote sensing image of a first time phase and a third remote sensing image of a second time phase, and respectively performing interpolation processing on the second remote sensing image and the third remote sensing image based on a preset algorithm to obtain two interpolation images; based on a preset rule, segmenting the first remote sensing image through a preset segmentation tool to obtain a plurality of segmented regions; for each segmented region in each segmented region, constructing a local regression model according to the two interpolation images, and obtaining a preliminary space-time fusion result corresponding to each segmented region according to the first remote sensing image and the local regression model; and according to the local regression model and the two interpolation images, obtaining a residual value of each pixel in each segmentation region, and according to the residual value and the initial space-time fusion result corresponding to each segmentation region, obtaining a target space-time fusion result corresponding to each segmentation region. 本发明公开了一种遥感影像数据对象级时空融合的方法，方法包括：获取第一时相的第一遥感影像和第二遥感影像，以及第二时相的第三遥感影像，并基于预设的算法，对第二遥感影像和第三遥感影像分别进行插值处理，得到两个插值影像；基于预设的规则，通过预设的分割工具将第一遥感影像进行分割，得到若干分割区域；针对各个分割区域中的每个分割区域，根据两个插值影像，构建局部回归模型，并根据第一遥感影像和局部回归模型，得到每个分割区域对应的初步时空融合结果；根据局部回归模型、两个插值影像，得到每个分割区域中每个像元的残差值，并根据残差值和每个分割区域对应的初步时空融合结果，得到每个分割区域对应的目标时空融合结果。