Digital twin image and real image registration method and device and readable storage medium

Abstract

The invention provides a digital twin image and real image registration method and device and a readable storage medium, based on Hough transformation, the digital twin image and real image registration method and device have the characteristics of strong anti-illumination and anti-distortion capabilities, and since the first reference straight line of the real image and the second reference straight line in the digital twin image are used as the reference for registration, the registration accuracy is greatly improved. And processing such as image conversion and correction is not needed, so that the registration precision is high, the generated fused image is clearer, and the service requirements are met.

Description

technical field [0001] The invention belongs to the technical field of image registration, and in particular relates to a registration method, device and readable storage medium between a digital twin image and a real image. Background technique [0002] With the rapid development of a new generation of information technology represented by big data, Internet of Things and artificial intelligence technologies, the digital upgrade of traditional industries is imminent. In the process of digital transformation of natural gas operating enterprises, in order to realize the visualization of LNG stations, three-dimensional modeling is generally used to construct virtual digital twin images. In order to fully display the details of the real scene, it is often necessary to register the digital twin images with the real images. , fusion. [0003] Because the collection of remote sensing images of LNG stations is easily affected by natural factors such as weather changes and light in...

AI Technical Summary

Problems solved by technology

[0003] Since the collection of remote sensing images of LNG stations is easily affected by natural factors such as weather changes and light intensity, the real images obtained are often blurred

Therefore, it is difficult to find the registration reference features when using the grayscale-based image registration algorithm to match the digital twin image of the LNG station with the real image, resulting in the generated fusion image being often blurred and difficult to meet business requirements

Image registration algorithms based on the frequency domain usually use the properties of image translation, rotation, and scaling in the frequency domain to solve the transformation parameters to achieve accurate matching of the two images. It is easy to introduce noise and errors after image transformation and correction, which will reduce the accuracy of image registration, and the generated fusion image will be blurred

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