DeepAI AI Chat
Log In Sign Up

Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization

by   Yoonsik Kim, et al.
Seoul National University

Real-noise denoising is a challenging task because the statistics of real-noise do not follow the normal distribution, and they are also spatially and temporally changing. In order to cope with various and complex real-noise, we propose a well-generalized denoising architecture and a transfer learning scheme. Specifically, we adopt an adaptive instance normalization to build a denoiser, which can regularize the feature map and prevent the network from overfitting to the training set. We also introduce a transfer learning scheme that transfers knowledge learned from synthetic-noise data to the real-noise denoiser. From the proposed transfer learning, the synthetic-noise denoiser can learn general features from various synthetic-noise data, and the real-noise denoiser can learn the real-noise characteristics from real data. From the experiments, we find that the proposed denoising method has great generalization ability, such that our network trained with synthetic-noise achieves the best performance for Darmstadt Noise Dataset (DND) among the methods from published papers. We can also see that the proposed transfer learning scheme robustly works for real-noise images through the learning with a very small number of labeled data.


Few-Shot Meta-Denoising

We study the problem of learning-based denoising where the training set ...

FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoising

Due to the fast inference and good performance, discriminative learning ...

Deep learning tutorial for denoising

We herein introduce deep learning to seismic noise attenuation. Compared...

Dual Diffusion Architecture for Fisheye Image Rectification: Synthetic-to-Real Generalization

Fisheye image rectification has a long-term unresolved issue with synthe...

Auto robust relative radiometric normalization via latent change noise modelling

Relative radiometric normalization(RRN) of different satellite images of...

Multiresolution Convolutional Autoencoders

We propose a multi-resolution convolutional autoencoder (MrCAE) architec...

Polynomial method for Procedural Terrain Generation

A systematic fractal brownian motion approach is proposed for generating...