A SegNet remote sensing image semantic segmentation method combined with random walk

A random walk and semantic segmentation technology, applied in the information field, can solve problems such as edge recognition and positioning errors of ground objects, edge segmentation is not smooth enough, and there are many plaque noises, etc., to achieve accurate edge positioning, optimize segmentation results, and improve output quality Effect
CN109409240AActive Publication Date: 2019-03-01BEIHANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIHANG UNIV
Publication Date
2019-03-01

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Abstract

The invention relates to a SegNet remote sensing image semantic segmentation method combined with random walk, which is divided into a SegNet initial segmentation step and a random walk optimization segmentation step. The SegNet initial segmentation step outputs an initial semantic segmentation image and category intensity information through the SegNet. A method for optimize segmentation of random walk includes selecte a random walk seed region, calculating classification saliency indexes of different class according to classified intensity information output by SegNet, and selecting seed regions of different classes by setting a threshold value; secondly, the undirected edge weights are calculated according to the original image gradient and SegNet classification intensity information. In the third step, starting from the seed region and combining with the undirected edge weights, the segmentation image is randomly walked on the whole initial segmentation image, and finally the optimized segmentation result on the whole image is obtained. The invention randomly walks on the whole image, realizes prediction error and control, greatly reduces edge burr and patch classification error, and completes high-precision remote sensing image semantic segmentation.
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Description

technical field

[0001] The invention relates to a SegNet (Random-Walk-SegNet) remote sensing image semantic segmentation method combined with random walk, which belongs to the field of information technology. Background technique

[0002] In recent years, remote sensing technology has developed rapidly, and remote sensing image processing technology is increasingly used in disaster analysis, urban monitoring, and resource management. Remote sensing image change detection is one of the key technologies. It can detect what changes have occurred in a specific area within a certain period of time and the degree of change based on images of different periods. Semantic segmentation is a core issue in remote sensing image change detection. , through semantic segmentation, the object category information to which each pixel in the image belongs can be obtained, and on this basis, the change information between the two images can be obtained by comparison.

[0003] Image semantic se...

Claims

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