Remote sensing image change detection method, electronic equipment and storage medium

Abstract

The invention discloses a remote sensing image change detection method. The method comprises the following steps: acquiring a remote sensing image; inputting the remote sensing image into a pre-generated deep learning model, wherein the depth model comprises an irregular image object depth feature extraction module and a depth feature fusion classification module, the depth feature extraction module is generated by pre-training an unsupervised stack type noise reduction automatic encoder, and the depth feature fusion classification module is composed of a pre-trained noise reduction automaticencoder, a cascade layer, a full connection layer and a logistic regression layer; receiving a change detection result graph generated by the deep learning model; and outputting a detection result according to the transformation detection result graph. In the training process of the learning model, a large amount of labeled data does not need to be used for training, so that the labor and time cost of deep learning is reduced, the edge and shape information of the irregular object can be kept by the deep learning model, and the depth features of the irregular image object can be expressed anddescribed.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a remote sensing image change detection method, electronic equipment and a storage medium. Background technique [0002] Remote sensing earth observation technology has become an important means of dynamic detection of land use / cover change. High-resolution remote sensing image change detection is to process and analyze multiple remote sensing images covering the same area acquired at different times to realize dynamic detection of changes in surface features. [0003] The current detection methods mainly include pixel-level change detection and object-oriented change detection. Since pixel-level change detection can reduce salt and pepper noise and speckle noise in the results, object-oriented change detection has been widely used, but object-oriented transformation The detection method is not highly automated, and still faces the problem of feature selection and sampl...

AI Technical Summary

Problems solved by technology

[0005] The main purpose of the present invention is to provide a remote sensing image change detection method, electronic equipment and storage medium, aiming to solve the problem that deep learning cannot directly express and describe the depth characteristics of irregular image objects in the prior art, and the human and time costs of deep learning are relatively high. high technical issues

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