Key Target Recognition in High Frame Rate Images Based on Multi-Scale Feature Fusion
To optimize the target recognition performance of high frame rate images,a key target recognition method based on multi-scale feature fusion is proposed for high frame rate images.Combining spatial bilateral fil-tering algorithm and dual tree complex wavelet transform algorithm to remove noises from high frame rate images.Extract image features through multiple convolutional modules and fus multi-scale features under branch spatial attention mechanisms and improved channel attention networks.Introduce the concept of joint sparsity to repre-sent the fused multi-scale features,and input them into the convolutional neural network structure for further learning,outputting key target recognition results.The experimental results show that the AUC value of the pro-posed method after application is 0.91,which meets the requirements of high frame rate image processing.
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