Remote sensing image target detection algorithm based on CenterNet

Abstract

Aiming at the problems of small target scale, vulnerable to background interference and insufficient feature utilization in remote sensing image target detection task, a single stage target detection algorithm based on feature enhancement and feature fusion is proposed. Based on CenterNet, a feature enhancement module is designed, which enriches and strengthens the features of small targets and solves the problem of low accuracy caused by small targets and background interference. Then BiFPN mini multi-scale feature fusion structure is used to strengthen the feature expression ability of the target and solve the problem of insufficient feature utilization. This algorithm is implemented in the average detection accuracy on UCAS_AOD dataset reaches 84.9%. The experimental results show that the improved measures in this paper effectively improve the target detection accuracy for remote sensing images.