  Fingerprint image denoising is a very important step in fingerprint
identification. to improve the denoising effect of fingerprint image,we have
designs a fingerprint denoising algorithm based on deep encoder-decoder
network,which encoder subnet to learn the fingerprint features of noisy
images.the decoder subnet reconstructs the original fingerprint image based on
the features to achieve denoising, while using the dilated convolution in the
network to increase the receptor field without increasing the complexity and
improve the network inference speed. In addition, feature fusion at different
levels of the network is achieved through the introduction of residual
learning, which further restores the detailed features of the fingerprint and
improves the denoising effect. Finally, the experimental results show that the
algorithm enables better recovery of edge, line and curve features in
fingerprint images, with better visual effects and higher peak signal-to-noise
ratio (PSNR) compared to other methods.
