Beijing University of Civil Engineering and Architecture

Ningning Qu

Jingguo Lv

Yifei Cao

Tingrui Hu

A method for detecting a dim and small object based on a discriminant feature of video satellite data is provided. The method makes full use of the discriminant feature to improve detection accuracy of the dim and small object. A symmetric semantic segmentation model and an autoencoder model are used to extract the discriminant feature of an object. A top-down adjustment mechanism is used to fuse an image feature and the discriminant feature of the object. Then an attention mechanism is used to enhance a background to further increase contrast between the object and the background. A multi-scale semantic analysis strategy is introduced, and a pyramid model is used to extract the dim and small object in the video satellite data.

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Beijing, China

Ningning Qu