Fine correction method and device for satellite space-time diagram, and storage medium

Abstract

The invention provides a fine correction method and device for a satellite space-time diagram, and a storage medium. The fine correction method comprises the following steps: acquiring a to-be-corrected remote sensing image and a reference remote sensing image, wherein the resolution ratios of the remote sensing image to be corrected and the reference remote sensing image are the same; respectively preprocessing the remote sensing image to be corrected and the reference remote sensing image to obtain a preprocessed remote sensing image to be corrected and a preprocessed reference remote sensing image, wherein the preprocessing comprises fuzzy processing and edge enhancement processing; respectively determining feature points in the preprocessed remote sensing image to be corrected and the preprocessed reference remote sensing image; and carrying out feature point matching on the feature points in the preprocessed remote sensing image to be corrected and the feature points in the preprocessed reference remote sensing image to obtain a finely corrected remote sensing image. The fine correction method is used for improving the correction efficiency and the correction precision of the remote sensing image.

Description

technical field [0001] The present application relates to the field of image processing, in particular, to a fine correction method, device and storage medium for a satellite space-time map. Background technique [0002] Remote sensing image correction is a process of superimposing and matching multiple remote sensing images with different resolutions, different sensors, different imaging times, different shooting angles and different imaging conditions. [0003] For the correction of grayscale information, due to the large image of the correction result due to the lighting conditions and image noise, and the grayscale information is a kind of overall information, the calculation speed is slow in the image matching process, resulting in low correction efficiency; and, the corrected The accuracy is also low; the correction of transform domain information is sensitive to noise and the amount of calculation is large, and it is suitable for the correction of low-noise remote sen...

AI Technical Summary

Problems solved by technology

[0003] For the correction of grayscale information, due to the large image of the correction result due to the lighting conditions and image noise, and the grayscale information is a kind of overall information, the calculation speed is slow in the image matching process, resulting in low correction efficiency; and, the corrected The accuracy is also low; the correction of transform domain information is sensitive to noise and the amount of calculation is large, and it is suitable for the correction of low-noise remote sensing images with little change; Radiation transformation invariance has always been a research hotspot in the field of image correction

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