Method and device for retrieving visible view from remote sensing image bare land

Abstract

The invention discloses a method and a device for inverting a visible image from a bare ground of a remote sensing image. The method includes: preprocessing the original remote sensing data to obtain the test image of the target geographic area and the RGB image of the target geographic area; using the first classification network model to perform pixel-level semantic segmentation on the test image of the target geographic area; using the second The classification network model selects the area outline of the test image after semantic segmentation; aligns and superimposes the selected area outline to the corresponding position on the RGB image of the target geographic area. The device includes a preprocessing unit, a semantic segmentation unit, a contour selection unit, and a contour output unit. The drawing of the bare land inversion map is fully automatic, which saves a lot of manpower, has generalization, and can be made into an interface and promoted to various cities. Full vector drawing, zooming in and out of the drawn picture will not affect the clarity of the outline and numbers, which is clearer than Arcgis manual drawing.

Description

technical field [0001] The present invention relates to the field of combined application of remote sensing images and deep learning technologies. More specifically, the present invention relates to a method and device for retrieving visual images from remote sensing images in bare land. Background technique [0002] Remote sensing is the imaging of the earth in a specific electromagnetic spectrum through the sensor on the satellite, and it is a technology developed on the basis of aerial photography technology. Through remote sensing detection, it is possible to conduct multi-level and multi-perspective observations on a large area of ​​the earth in a short period of time, which is an important means of obtaining environmental information and earth resources. [0003] Bare land refers to land whose surface is soil and basically no vegetation coverage or land whose surface is rocks and gravels and whose coverage area is greater than or equal to 70%. Bare land includes unuse...

AI Technical Summary

Problems solved by technology

Manually interpret and correct the bare land areas generated by deep learning, and use Arcgis and other labeling software to draw the generated bare land. The labor cost is too large, time-consuming and labor-intensive, it is difficult to promote, and it is not suitable for popularization

[0006] In the prior art, in the method for displaying the results of bare land inversion of remote sensing images, it is mainly to artificially use the Arcgis software tool to manually classify the obtained bare land categories, and to correct and draw through manual experience. The disadvantages of this method are: 1) Arcgis software can only process rgb band images. For multi-band data, other software such as ENVI needs to be used cross-use, and it has high hardware requirements, and it is easy to fill up the computer memory, causing the computer to freeze, which takes a long time and is inefficient; 2) only processing It takes about 4 days to invert a visual map of bare land in a prefecture-level city. Since bare land inversion maps are often used in bare land management, drawing all target cities requires a lot of human labor

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