Remote sensing image classification method of double-branch fusion multi-scale attention neural network

Abstract

The invention discloses a remote sensing image classification method of a double-branch fusion multi-scale attention neural network. The method comprises the following steps: reading a multispectral image from a data set; after an image matrix is obtained, preprocessing image data by using superpixels; performing normalization operation on the data, and taking a block from each pixel in the normalized image matrix to form an image block-based feature matrix; selecting a training set and a test set; constructing a classification model of the convolutional neural network based on two-channel sparse feature fusion; training the classification model by using the training data set; and utilizing the trained classification model to classify the test data set. According to the method, consideringfrom the characteristics of the image, the characteristics can be extracted by self-adapting to the size of the target region object in the image, and a new central pixel offset strategy is adopted for the boundary pixels, so that the classification accuracy of the boundary pixels is improved, and the operation speed of the whole training process is also improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a remote sensing image classification method based on center pixel migration, double-branch fusion and multi-scale attention neural network, which can be used for land resource investigation, land use and land cover, urban and rural planning, environmental monitoring, In related fields such as tourism development and other remote sensing image target area classification. Background technique [0002] With the continuous development and progress of satellite remote sensing and aerial remote sensing technology, we can obtain the desired information from the obtained remote sensing images in various ways and apply them to our lives to facilitate people. For the obtained multispectral (MS) remote sensing image and high-resolution panchromatic (PAN) remote sensing image in the same scene, since the MS image has a narrow spectral range, and the PAN image has richer...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a remote sensing image classification method based on the central pixel migration dual-branch fusion multi-scale attention neural network to solve the problems of low classification accuracy and inability to adapt to the existing technology. The problem of classifying objects of various sizes

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