Multi-stage image denoising with the wavelet transform. (arXiv:2209.12394v2 [eess.IV] UPDATED)

Deep convolutional neural networks (CNNs) are used for image denoising via
automatically mining accurate structure information. However, most of existing
CNNs depend on enlarging depth of designed networks to obtain better denoising
performance, which may cause training difficulty. In this paper, we propose a
multi-stage image denoising CNN with the wavelet transform (MWDCNN) via three
stages, i.e., a dynamic convolutional block (DCB), two cascaded wavelet
transform and enhancement blocks (WEBs) and residual block (RB). DCB uses a
dynamic convolution to …

arxiv denoising image stage