Research on small target detection algorithm under complex conditions

Small target detection is one of the most challenging tasks in image processing.In order to solve the problem of insufficient accuracy of small target detection under complex conditions,this paper proposes to reconstruct the captured blurred image by using the super-resolution model,and to detect the reconstructed clear image for small target.In addition,the original FPN model is improved,and rich location information of the shallow target network is used,and only the three-layer feature extraction network is used to complete the small target full-image search detection.Experiments show that the accuracy of this method is 81.82% and the map value is 0.895 1.The reconstructed small target detection and clear image direct detection have only one undetected difference.