Convolutional neural network-based detector for random-valued impulse noise
Shaoping Xu, Guizhen Zhang, Lingyan Hu, Tingyun Liu · Journal of Electronic Imaging · 2018
A shallow yet effective convolutional neural network (CNN)-based detector was proposed for automatic detection of random-valued impulse noise (RVIN) from images. We guided the proposed CNN-based detector to automatically extract the implicit statistics and learn the detection mechanism with a large number of patches and their corresponding noise labels regarding center pixels. Compared with the reference RVIN detectors, the proposed CNN-based one takes advantage of the prior knowledge obtained in the training phase and shows impressive detection accuracy across different noise ratios.