Moving object detection algorithm based on image enhancement technology
The multi-weight joint loss function is used to restore image details to solve the problem of blurred details caused by low image contrast;Aiming at the problem that the optical flow network has many input parameters in image feature extraction,a hollow residual network is proposed as the feature extraction module of the image,and the feature extraction speed is improved by increasing the receptive field of the convolution kernel.In this paper,the COCO data set is used for training and testing.The experimental results show that compared with the existing similar algorithms,the optical flow field image obtained by the algorithm in this paper has higher definition,which effectively improves the detection accuracy and reduces the feature extraction time.
image enhancementobject detectionempty residual networkjoint loss function
NETL
NSTL
万方数据
