Construction method of remote sensing image classification model, remote sensing image classification method and system

Abstract

The invention provides a method for constructing a remote sensing image classification model, a remote sensing image classification method and system: step 1: collecting high-resolution remote sensing images; step 2: marking high-resolution remote sensing images to obtain high-resolution images with annotations Ratio remote sensing image, obtain the label set, segment the obtained high-resolution remote sensing image with labels to obtain the parent object, and segment the parent object to obtain the child object; step 3: standardize the parent object and child object obtained in step 2 , and divide the standardized parent object and child object into training sample set, verification set and test sample set; Step 4: Construct a convolutional neural network model based on parent object and child object. Then the network model is used to classify the high-resolution remote sensing images. The invention realizes the refined classification of geographic entities, and solves the problems of low classification precision, salt and pepper phenomenon and serious misclassification in the classification of high-resolution remote sensing images in complex scenes.

Description

technical field [0001] The invention belongs to the field of remote sensing and digital image processing, and relates to high-resolution remote sensing image classification, in particular to a method for constructing a remote sensing image classification model, a remote sensing image classification method and a system. Background technique [0002] With the development of remote sensing sensors and imaging technology, the resolution of remote sensing images is getting higher and higher. Classification of high-resolution remote sensing images is a key issue in the analysis and application of satellite image data. Deep learning, by extracting more abstract features layer by layer from the input data from the low level to the high level, forms a network weight structure that is most suitable for the required features, thereby improving the accuracy of classification and enabling the classification model to have classification generalization capabilities. Among them, convolutio...

AI Technical Summary

Problems solved by technology

[0004] In view of the deficiencies and defects of the above-mentioned prior art, the object of the present invention is to provide a method for constructing a remote sensing image classification model, a remote sensing image classification method and system, and solve the problems in the classification of high-resolution remote sensing images in complex scenes in the prior art. , low classification accuracy, salt and pepper phenomenon and serious misclassification problems

Images