Deep learning-based remote sensing image semantic segmentation method

Abstract

The invention discloses a deep learning-based remote sensing image semantic segmentation method. The method comprises the steps of assigning an RGB value and a gray value to each target species, obtaining an original remote sensing image, selecting a target species to color and gray the target species, imparting a gray value to the target species to obtain a label image, and subjecting the original remote sensing image to data enhancement and edge extraction to obtain an edge-extracted image; training a full convolution neural network by adopting the original remote sensing image and the imagetraining sample of the edge-extracted image to obtain an optimum semantic segmentation network model, and inputting a to-be-tested remote sensing image into the optimum semantic segmentation networkmodel to obtain a semantic segmentation result image; coloring the semantic segmentation result image to obtain a final semantic segmentation result image, and obtaining a species target according toRGB values in the final semantic segmentation result image. According to the method, the semantic segmentation results of remote sensing images are high in accuracy, and the method is wide in applicability.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for semantic segmentation of remote sensing images based on deep learning. Background technique [0002] Image semantic segmentation combines the traditional image segmentation and target recognition tasks. Its purpose is to divide the image into several groups of pixel areas with a certain semantic meaning, and identify the category of each area, and finally obtain a picture with pixel Semantically annotated images. This technology is one of the three core research issues of computer vision, and it is a very challenging research direction in the field of computer vision and pattern recognition. The biggest difference between image semantic segmentation and image segmentation is that image segmentation only completes image pixel clustering, while image semantic segmentation further identifies categories after completing pixel clustering and gives category seman...

AI Technical Summary

Problems solved by technology

However, for remote sensing images, due to the difficulty in obtaining data and low image clarity, these two characteristics make it impossible to achieve satisfactory results through the above traditional methods for the semantic segmentation task of remote sensing images.

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