Rapid detection and correction method for local distortion of remote sensing image along rail direction

Abstract

The invention discloses a rapid detection and correction method for local distortion of a remote sensing image along a rail direction. The method comprises the following steps: acquiring an imaging time data file and a meta-information file of a to-be-detected image; extracting information of a to-be-detected image from the meta-information file, wherein the information of the to-be-detected image comprises a scene number of the to-be-detected image, an image starting absolute line count and an image ending absolute line count; obtaining the integral time recorded in each line from the image starting absolute line counting to the image ending absolute line counting from the imaging time data file according to the scene number, and judging whether the integral time corresponding to each line jumps line by line; if the to-be-detected image jumps, early warning information is generated, outputting information of the to-be-detected image and row count and integral time of jumping, wherein the early warning information is used for indicating that local distortion of the to-be-detected image can occur in the rail direction. The technical problem of low detection efficiency and accuracy in the prior art is solved.

Description

technical field [0001] The present application relates to the technical field of remote sensing image detection, in particular to a rapid detection and correction method for local distortion of remote sensing images along the track. Background technique [0002] The Gaojing-1 satellite's Charge Coupled Device (CCD) device focal plane stitching camera uses 4 panchromatic multi-spectral five-color TDICCDs to stitch the mirrors into a straight line. According to the precise real position of each detector element in each spectral segment of each CCD device in the camera, the imaging time data, integration time data, attitude data, orbit data and scene cataloging information data of each row of images, sensor calibration is performed to construct each detector element Observation vectors, uniformly solve problems such as geometric distortion, geometric splicing, imaging time normalization, and band registration, and realize the unification of the resolution of each detector eleme...

AI Technical Summary

Problems solved by technology

[0005] The technical problem solved by this application is: to solve the problem of low detection efficiency and accuracy in the prior art, this application provides a rapid detection and correction method for local distortion of remote sensing images along the track direction. The embodiment of this application provides In the solution, on the one hand, automatic detection is used to avoid the problems of large number of images and low detection efficiency and accuracy caused by manual detection; on the other hand, it is avoided to obtain feature points with the same name through SIFT algorithm, mutual information or phase consistency In the process of automatic image matching and detection, there may be bad pixels in each band of the camera, several grayscale resamplings in the process of image radiation geometry processing, or the texture of water and desert images is relatively simple, and the texture of farmland and woodland images is relatively large. Reasons such as fragmentation affect the accuracy of automatic matching, resulting in the problem of false detection

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