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There are several previous methods based on neural network can have greatperformance in denoising salt and pepper noise. However, those methods arebased on a hypothesis that the value of salt and pepper noise is exactly 0 and255. It is not true in the real world. The result of those methods deviatesharply when the value is different from 0 and 255. To overcome this weakness,our method aims at designing a convolutional neural network to detect the noisepixels in a wider range of value and then a filter is used to modify pixelvalue to 0, which is beneficial for further filtering. Additionally, anotherconvolutional neural network is used to conduct the denoising and restorationwork.

A Two-stage Method for Non-extreme Value Salt-and-Pepper Noise Removal