Efficient labeling method and system for high-resolution remote sensing target big data set

Abstract

The invention discloses a high-efficiency labeling method and system for a high-resolution remote sensing target big data set. The method comprises the following steps: intercepting an image picture on each obtained high-resolution remote sensing image according to a preset condition; creating an image picture creation engineering vector file; labeling attributes on the vector layer on the engineering vector file; judging the target object type of the labeling position according to the labeling attribute; marking the selected target objects according to different types of the target objects; storing the marked engineering vector file; judging whether labeling information of other types of images exists or not, and if yes, corresponding the engineering vector file with the labeling box to the multispectral image and the fused image; or, if not, storing the final labeling result. A complete system for marking the target object is formed, marking can be conducted on the panchromatic imagewith the highest resolution ratio, finally, the panchromatic image corresponds to the multispectral image and the fusion image, marking is more attached to the target object, and marking is faster and more accurate.

Description

technical field [0001] The present application relates to the technical field of remote sensing image processing, in particular to a method and system for efficient labeling of large datasets of high-resolution remote sensing targets. Background technique [0002] In recent years, high-resolution remote sensing images have been widely used in government management, people's life and military affairs. Object detection, as a key step, can provide the location of the region of interest and change the detection result. Building detection in remote sensing images requires manual labeling of a large number of various building samples, and accurate labeling boundary adjustments must be made for irregular buildings. However, the traditional method of target labeling in remote sensing images connects the work of each stage, which brings difficulties to manual labeling of high-density and large-scale remote sensing targets. [0003] For remote sensing image analysis, there have been...

AI Technical Summary

Problems solved by technology

And there are problems such as researchers being unable to annotate during the fusion stage, and the resolution of the fusion image is reduced, resulting in a reduction in annotation accuracy

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