SAR image registration method based on straight lines and FFT

Abstract

The invention belongs to the technical field of image processing, and particularly provides an SAR image registration method based on straight lines and an FFT to mainly solve the problems that an existing technology is poor in registration effect and high in computing complexity. The method comprises the first step of inputting two SAR images and detecting the straight lines of the two images through a margin fitting method, the second step of carrying out statistics on the detected straight lines according to a slope difference histogram and calculating rotating parameters, the third step of carrying out the Fourier transform on a reference image and a rotated image to be registered to obtain a Fourier transform diagram, the fourth step of calculating horizontal movement parameters through the Fourier phase correlation method, and the fifth step of enabling the horizontally-moved and rotated image to be registered to coincide with the reference image and finishing the registration. The SAR image registration method has the advantages that the effect degree on the registration of the SAR images from noise is small, the registration result of the SAR images with abundant linear features is stable, the registration effect is better, speed is high, and the computing complexity is low, and the SAR image registration method can be used for pattern recognition, automatic navigation and computer vision and remote sensing image process.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to edge extraction and phase information of a synthetic aperture radar SAR image, which can be used for SAR image registration, and specifically provides a SAR image registration method based on a straight line and FFT. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution active microwave remote sensing imaging radar. It has the advantages of all-weather, all-time, high resolution, and side-view imaging. It can be used in military, agricultural, navigation, geographic surveillance, etc. field. Image matching can be divided into three categories: matching methods based on gray correlation, matching methods based on features and matching methods based on mutual information. [0003] The method based on gray-scale correlation is a way to search and match images with a certain size of Dido array in order of one or several similarity measures. Once this ...

AI Technical Summary

Problems solved by technology

The process of image acquisition and feature extraction will produce different degrees of noise, making it difficult to determine the correspondence between the original accurate point features.

[0005] The template matching algorithm based on mutual information has the advantages of high matching accuracy, anti-occlusion, anti-random noise, etc., and has been widely used in the field of image registration, but the calculation amount of standard mutual information is very large, and it is difficult to achieve real-time matching; and, mutual information The measurement loses a lot of image space information, which will lead to problems such as the maximum mutual information is not unique or the maximum position is inconsistent with the image registration position.

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