Remote sensing scene classification method and system based on multi-scale feature fusion

Abstract

The invention relates to the technical field of image processing, and discloses a remote sensing scene classification method and system based on multi-scale feature fusion. The method comprises the steps: obtaining the image features of a collected remote sensing image under different scales, inputting the image features into a preset convolutional neural network model, and carrying out the multi-scale feature fusion, obtaining fusion features, obtaining bottom-layer features of a remote sensing image, carrying out normalization processing on the bottom-layer features and the fusion features to obtain target features, and inputting the target features into a preset classifier to carry out scene classification so as to obtain the category of the remote sensing image, inputting image features of an obtained remote sensing image under different scales into a preset convolutional neural network model to obtain fusion features, then performing normalization processing on the fusion features and bottom-layer features to obtain target features, and realizing remote sensing scene classification based on the target features. The phenomena of high inter-class similarity and large intra-class difference are avoided, and the remote sensing image classification precision and accuracy are improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a remote sensing scene classification method and system based on multi-scale feature fusion. Background technique [0002] Remote sensing images provide an important data basis for humans to analyze and observe the earth's surface. However, because most of them cooperate with different remote sensing satellites to complete the observation of the earth's surface, remote sensing images have the following characteristics: (1) Remote sensing images cover a wide range, including large amount of information; (2) large intra-category differences, that is, the texture, shape and color of remote sensing images of the same category of ground object types are significantly different in texture, shape and color; (3) high similarity between classes, that is, remote sensing images of different types of ground object types Images are familiar in texture, shape, and color. Based on thi...

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a remote sensing scene classification method and system based on multi-scale feature fusion, aiming at solving the technical problem of how to improve the precision and accuracy of remote sensing scene classification

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