River and lake remote sensing image segmentation method and system based on convolutional neural network and Transform

Abstract

The invention discloses a river and lake remote sensing image segmentation method and system based on a convolutional neural network and Transform, and the method comprises the steps: obtaining a river and lake remote sensing image containing a class label, and constructing a training set; extracting a multi-layer feature map from the training set by using a convolutional neural network; extracting an attention feature from the last layer of extracted feature map by adopting a Transform encoder, and obtaining a self-attention feature map from the attention feature by adopting a Transform decoder; after the self-attention feature map and the first-layer feature map are spliced, training an image segmentation model; and obtaining a category segmentation result of the target in the remote sensing image of the river and lake to be detected based on the trained image segmentation model. Transform is introduced into the field of remote sensing image segmentation, a self-attention mechanism is used for replacing convolution operation, the receptive field area during operation is enlarged, due to the fact that down-sampling and up-sampling operation does not exist, image scale change cannot be caused, the problem of target loss is solved, and the defects of an existing deep learning segmentation method in the field of remote sensing image segmentation are overcome.

Description

technical field [0001] The invention relates to the technical field of convolutional neural networks and remote sensing images, in particular to a method and system for segmenting river and lake remote sensing images based on convolutional neural networks and Transformers. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] The "four chaos" of rivers and lakes refers to the phenomenon of "random construction, random occupation, random mining, and random piles" around rivers and lakes. The areas around rivers and lakes have been banned repeatedly, seriously affecting the ecological environment of urban rivers and lakes and the quality of life of nearby residents. The rectification of the "four chaos" in rivers and lakes has become the main content of the supervision of urban rivers and lakes. [0004] At present, the illegal extraction method...

AI Technical Summary

Problems solved by technology

Since the remote sensing data is generally collected by satellites or drones, and the "four chaos" phenomenon around rivers and lakes generally covers a small area, the target may be lost after multiple downsampling, thus affecting the accuracy of segmentation. Therefore, under the premise of not affecting the segmentation accuracy and avoiding the loss of targets, it is a very challenging problem to identify small areas of "chaos" in rivers and lakes from remote sensing images.

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