Study On Weighted Mean Filtering Algorithm Based On The Images With Salt And Pepper Noise

Image restoration is an important research topic in the area of image restoration. Its objective is to restore the lost information according to around image information. The images with salt and pepper noise is a special kind of image, denoising is a basic content in image pre-processing and denoising salt-pepper noise is an important part of it. In view of denoising salt-pepper noise, a adaptive weighted mean filter based on decomposition of histograms is proposed in this thesis. In this paper several methods for filtering the salt-pepper noise are first introduced. Then discussion is focused on weighted mean filter based on decomposition of histograms and adaptive weighted mean filter. The advantages and disadvantages of two methods for a adaptive weighted mean filter based on decomposition of histograms is proposed. In the adaptive weighted mean filter based on histogram decomposition, first of all use of the image point of the distribution of the characteristics of directional, pull in the salt and pepper noise points to a pre-judgment; Then the weighting coefficient is determined after an orthogonal decomposition of the original image histogram using the properties of Gaussian distribution. The experimental results show that this improved method is simple and effective.