A Change Detection Method Based on High Resolution Remote Sensing Image

Abstract

The invention discloses a change detection method based on high-resolution remote sensing images. Firstly, after necessary preprocessing such as orthorectification, image registration, and histogram matching, the method uses superpixel segmentation and synthesis The remote sensing image is divided into blocks, and the calculation of local features and sample selection are performed in units of superpixels, so as to realize the automatic labeling of the changed or unchanged areas with obvious tendencies in the image; after that, the twin convolution is trained with the labeling results as samples The neural network classifies the image changes, and performs post-processing such as noise reduction and morphological filtering to obtain the final change detection results. Experiments show that on the Gaofen-2 satellite remote sensing image data set, the indicators of the method of the present invention are much better than the traditional change detection algorithm, the Kappa coefficient is increased by 0.3 on average, the average overall error rate is lower than 3.5%, and the detection results have more High practical value.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image recognition and deep learning, and in particular relates to a change detection method based on high-resolution remote sensing images. Background technique [0002] In recent years, satellite technology has achieved rapid development, and the application fields of satellite remote sensing images have also been continuously expanded, playing an important role in meteorology, geology, surveying and mapping, agriculture, forestry, animal husbandry and fishery, military reconnaissance and other fields. Remote sensing image change detection refers to the use of remote sensing images in the same area at different times and related data such as atmosphere and sensors, after image correction and other preprocessing, and with the help of mathematical statistics or artificial intelligence related technologies, feature extraction and comparison of remote sensing images, and Analyze and judge its ...

AI Technical Summary

Problems solved by technology

[0005] Although high-resolution multispectral satellite remote sensing images contain more information, they also introduce numerous interference factors and technical challenges. How to fully and reasonably use the information contained in the images and effectively reduce the impact of various interference factors on The impact of analysis is an urgent problem to be solved in change detection; the introduction of deep learning theory and methods has proposed new ideas for the optimization of change detection algorithms

[0006] In the learning process of the neural network, the importance of data is irreplaceable; the amount of data of remote sensing satellite images is very large, and the change itself lacks an objective definition, and may change with the change of the application scene. Labeling is not only a lot of work but also very difficult

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