Change detection method based on high-resolution remote sensing image

A remote sensing image and change detection technology, applied in the field of remote sensing image recognition and deep learning, can solve the problems of large workload, difficulty and lack of objective definitions for accurate data labeling, and achieve the effect of low overall error rate and improved accuracy.

Active Publication Date: 2018-09-25
ZHEJIANG UNIV
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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 learn

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Embodiment Construction

[0035] In order to describe the present invention more specifically, the technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] like figure 1 As shown, the change detection method of the high-resolution remote sensing image of the present invention specifically includes the following steps:

[0037] (1) Preprocessing of high-resolution remote sensing images.

[0038]Remote sensing imaging is very susceptible to external factors such as sensor attitude changes, satellite platform movement, earth curvature, terrain fluctuations, optical system distortion, etc., resulting in distortion, offset, extrusion, stretching, etc. of the captured remote sensing images relative to the real ground position. type of geometric distortion. Before using high-resolution remote sensing images for change detection, the remote sensing images must be preprocessed first. For different types of ...

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Abstract

The invention discloses a change detection method based on a high-resolution remote sensing image. The method is characterized by using a superpixel segmentation and synthesis algorithm to segment a multi-temporal remote sensing image after carrying out necessary ortho-rectification, image registration, histogram matching and other preprocessing, using a superpixel as a unit to carry out local characteristic calculating and sample selection, and realizing the automatic annotation of a changing area possessing an obvious tendency or an unchanged area in the image; and then, taking an annotationresult as a sample to train twinborn convolutional neural networks, classifying image changing conditions, carrying out noise reduction, morphological filtering and other postprocessing, and acquiring a final changing detection result. An experiment shows that in a high-score number-two satellite remote sensing image data set, each index in the method is better than each index in a traditional change detection algorithm; a Kappa coefficient is averagely increased by 0.3; and an average overall error rate is less than 3.5%. The detection result has a 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 ...

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Application Information

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IPC IPC(8): G06K9/62G06K9/32G06N3/04G06T7/11
CPCG06T7/11G06T2207/10032G06V10/25G06V10/758G06N3/045G06F18/2411G06F18/214
Inventor 罗智凌赵景晨尹建伟李莹吴朝晖
Owner ZHEJIANG UNIV
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