Automatic ortho-rectification method based on remote-sensing image of environmental No.1 satellite

Abstract

An automatic ortho-rectification method based on a remote-sensing image of an environmental No.1 satellite comprises the following steps of: (1) eliminating projection distortion caused by ground fluctuation in a reference image according to a geometric projection transformation principle to generate a simulated projection image; (2) finding possible feature points in the reference image and an original image by utilizing a Harris corner extraction algorithm; (3) finding possible homonymy points on the basis of the step (2) with a correlation coefficient method; (4) solving a relation coefficient between the reference image and the original image by using a polynomial model based on least squares; and (5) correcting the original image by utilizing the relation coefficient between the reference image and the original image, and eliminating the distortion caused by the ground fluctuation according to the geometric projection transformation principle again, so as to finally finish ortho-rectification. The method has the characteristics of high automation degree, no need of manually selecting control points, high correction precision and high production efficiency.

Description

technical field [0001] The invention relates to an automatic orthorectification method based on the remote sensing image of the Environment-1 satellite, which belongs to the technical field of remote-sensing image processing, and is suitable for the precise positioning of the remote-sensing image of the Environment-1 satellite, the extraction of image information and the preprocessing work of the production of special products, etc. . Background technique [0002] During the imaging process of satellite imagery, it is affected by many factors such as projection, camera axis tilt, earth curvature, and terrain fluctuations, resulting in different degrees of geometric deformation and distortion of each image point in the image. The orthorectification image can eliminate the image distortion caused by various factors in the imaging process, and restore a remote sensing image with accurate geographical location. Therefore, orthorectification of remote sensing images has become a...

AI Technical Summary

Problems solved by technology

However, stereo images are not easy to obtain for remote sensing images, the cost is high, and a certain number of control points need to be manually selected.

For the few existing remote sensing image automatic correction methods that use image matching and general empirical models, they only use corner point matching and quadratic polynomial models to apply them simply, and a fixed threshold needs to be set in each step. flexible, poor applicability

[0004] The shortcomings of the above methods are mainly reflected in: (1) manual selection of control points is required, and the process of selecting control points is extremely cumbersome, which greatly reduces the efficiency of image orthorectification; (2) due to the high dependence on manual work, the image correction The accuracy is uncontrollable and greatly affected by manual work; (3) stereo images are difficult to obtain for remote sensing images, and the cost is high; (4) the universality of thresholds in existing automatic correction methods is not high, and the calculation efficiency and calculation The precision of the result cannot be improved

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