Robust multi-source satellite remote sensing image registration method

Abstract

The invention discloses a robust multi-source satellite remote sensing image registration method based on mutual information and block random sample consensus. The method includes the following steps: (A) each layer of pyramid images are generated, and feature points are extracted; (B) on the highest layer of pyramid images, the global registration method is utilized to calculate affine transformation coefficients between the reference image and the slave image, and a rotation angle and a resolution difference coefficient between the images are estimated; (C) the initial positions of homonymy points are accurately predicted, geometric rough correction is carried out on matching window images, and normalized mutual information is utilized to search homonymy points; (D) a quadratic polynomial and a block RANSAC algorithm are utilized to eliminate false matching points; (E) step C and step D are repeated until the original image layer, and accurate image registration is implemented on the basis of the linear rubber sheeting method. The method greatly reduces the workload of manual editing in homonymy point measurement, increases the multi-source satellite remote sensing image data processing automation degree, and can bring remarkable economic and social benefits.

Description

technical field [0001] The invention belongs to the technical field of photogrammetry and remote sensing, and relates to a robust multi-source remote sensing image registration method. This method is based on mutual information image matching and block random sampling consistency technology, which can effectively solve the problem that it is difficult to automatically obtain the same point in multi-source satellite remote sensing images, and realize accurate registration of multi-source satellite remote sensing images. technical background [0002] With the rapid development of earth observation technology, satellite sensors are becoming more and more diverse. In recent years, high-resolution remote sensing satellites have emerged continuously. Optical remote sensing satellites include Ikonos, Quickbird, GeoEye, and WorldView, and SAR remote sensing satellites include TerraSAR-X, Cosmo-Skymed, and Radarsat-2. High-resolution satellite sensors have been widely used in terrai...

AI Technical Summary

Problems solved by technology

[0006] In view of the current automatic registration process of multi-source satellite remote sensing images, there are many wrong matching points, and manual elimination of wrong matching points is time-consuming and laborious. The purpose of this invention is to provide a method based on mutual information and random sampling of blocks The revolutionary multi-source remote sensing image registration method realizes the automatic, reliable and accurate matching of points with the same name, greatly improves the automation of satellite image registration, and greatly reduces the manual workload

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