Fast geometric correction method for satellite remote sensing image and based on control point image database

Abstract

A fast geometric correction method for a satellite remote sensing image and based on a control point image database comprises the following steps: the geographical scope of an image to be corrected is determined; all control points which meet requirements are retrieved in the control point image database according to the determined geographical scope of the image to be corrected; automatic matching and point selection are conducted, and control point pairs used for geometric correction are determined; whether the number and the distribution of the matched control point pairs meet the requirements of the geometric correction is judged, if the judging result is yes, the next step is conducted, and if the judging result is no, the retrieval step is conducted again; a geometric correction model is selected according to the type and imaging features of a sensor; a transformational relation between a pixel coordinate and a geodetic coordinate is established based on the matched control point pairs and the selected geometric correction model; and the geometric correction is conducted based on a digital elevation model and the transformational relation so as to obtain a corrected digital orthoimage. According to the fast geometric correction method for the satellite remote sensing image and based on the control point image database, the automatic image matching technique is introduced into automatic selection of the control points, and automatic geometric correction processing of the satellite remote sensing image can be realized.

Description

Technical field [0001] The invention relates to a method for correcting remote sensing images, more specifically to a method for rapid geometric correction of satellite remote sensing images based on a control point image database. Background technique [0002] With the development of remote sensing technology, especially the continuous development of remote sensing sensor technology, the use of remote sensing images or data obtained through remote sensing technology is becoming wider and wider. At present, the application scope of remote sensing data has been extended to the field of social information services, for example, widely used in surveying and mapping, agriculture, forestry, geology and minerals, hydrology and water resources, environmental monitoring, natural disasters, regional analysis and planning, military, land use, etc. aspect. Remote sensing images with precise geocoding can provide the features and information required by different fields such as land, planni...

AI Technical Summary

Problems solved by technology

[0006] The control points in the traditional operation process generally adopt the mode of full-field survey, which needs to go through a series of complicated procedures such as "collecting existing control data, surveying the survey area, selecting points for burying stones, field surveying, and internal sorting". With the development of advanced measurement technologies such as GPS-RTK, the workload and complexity of field surveys have been greatly reduced, but the necessary control point field survey work is still inevitable

[0007] In addition, due to the large coverage of satellite remote sensing images (taking Ziyuan-3 satellite as an example, the coverage area is 50 kilometers × 50 kilometers), in order to obtain evenly distributed ground control points, it usually needs to be located in hundreds of kilometers or even thousands of square kilometers It is self-evident that the field workload, manpower and material resources are huge if the measurement is carried out within the scope

In addition, in areas prone to natural disasters such as earthquakes, floods, and mudslides, or in inaccessible areas such as virgin forests, swamps, and deserts, surveyors are often unable to enter the field for measurement

[0008] Even if the control points are obtained by manually selecting points with the same name in remote sensing images and topographic maps, there are still problems such as low efficiency and difficult to guarantee accuracy.

However, when correcting different time phases or different sensor images in the same area, there will be repeated point selection.

Images