Multi-scale feature fusion remote sensing image segmentation method, device, equipment and memory

Abstract

The invention relates to a multi-scale feature fusion remote sensing image segmentation method and device, equipment and a memory. The method comprises the following steps: collecting a remote sensing image, and marking to obtain a training sample; a multi-scale feature fusion remote sensing image segmentation network is constructed, and the network comprises an input network which is used for segmenting a training sample into small blocks with fixed sizes, expanding the small blocks into one-dimensional vectors and embedding position codes to obtain an input sequence; the encoder is used for extracting different levels of an input sequence by utilizing a multi-layer Transform module; the decoder is used for prediction result by fusing the multi-scale feature map; and training the network by using a training sample to obtain a trained multi-scale feature fusion remote sensing image segmentation model, and obtaining a prediction result of a to-be-detected remote sensing image by using the model. According to the method, a multi-scale feature map extracted by an encoder is fully utilized, local classification and hierarchical segmentation are combined, and the method can adapt to the characteristic that targets in remote sensing images are complex and changeable.

Description

technical field [0001] The present application relates to the technical field of remote sensing image processing, in particular to a multi-scale feature fusion remote sensing image segmentation method, device, equipment and memory. Background technique [0002] With the continuous development of remote sensing detection technology, a large amount of high-resolution remote sensing image data can be obtained. Semantic segmentation of remote sensing images is one of the means of processing remote sensing image data. This method has many applications in forest cover detection, urban change detection, urban planning, crop monitoring, etc. Remote sensing image segmentation is a specific task in semantic segmentation. Segmenting remote sensing images can extract rich information contained in it for researchers to use. Therefore, the performance of image segmentation determines the quality of information extraction. Remote sensing images contain rich category information and irregu...

AI Technical Summary

Problems solved by technology

However, studies have shown that once a certain depth is reached, the benefit of adding more layers diminishes rapidly

Therefore, the limited receptive field of the general CNN structure is an inherent limitation of the FCN architecture, which affects the segmentation effect of remote sensing images.

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