A multi-source satellite remote sensing image mosaic method, system and storage medium

Abstract

The invention provides a multi-source satellite remote sensing image mosaic method, system and storage medium, respectively preprocessing the original high-resolution satellite remote sensing image and the original medium-resolution satellite remote sensing image, extracting the high-resolution satellite remote sensing image and the medium-resolution image The common band of satellite remote sensing images, as well as down-sampling of high-resolution satellite remote sensing images and super-resolution reconstruction of medium-resolution satellite remote sensing images, the resolution of the two is unified, and finally the same resolution of high-resolution Satellite remote sensing images and medium resolution satellite remote sensing images are mosaiced to generate mosaic lines to identify targets in the images. The present invention combines down-sampling and super-resolution reconstruction technologies to mosaic multi-source satellite remote sensing images, which not only retains the rich spatial information and spectral characteristics of high-resolution satellite images to a certain extent, but also uses medium-resolution satellite images as data supplements to solve the problem. Solved the problem of insufficient data volume of high-resolution images in industrial applications.

Description

technical field [0001] The present invention relates to the field of remote sensing images, and more specifically, to a multi-source satellite remote sensing image mosaic method, system and storage medium. Background technique [0002] With the continuous development of space information technology, a variety of satellite sensors with high resolution, hyperspectral, and multi-temporal phases have been launched one after another. In order to further promote the development of remote sensing technology and apply it to land and natural resources, crop growth, disaster monitoring, and environmental changes Possibilities are offered in areas such as monitoring and water conservancy. How to achieve high-quality and in-depth comprehensive application of satellite remote sensing images with multiple spectral and spatial resolutions, and maximize the acquisition of rich spatial, spectral, texture and other feature information contained in various data sources is one of the research f...

AI Technical Summary

Problems solved by technology

[0003] In the actual application of high-quality remote sensing images, due to the influence of many factors such as shooting range, revisit cycle, color, weather, and time, for a single satellite data source, the area of ​​the research area is large or small , but there are some clouds, mountains or vegetation shadows in the captured images, which will lead to incomplete coverage information of the target area

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