Removal of Random-valued Impulse Noise from Images Using Geometric Structure Detection
利用几何结构检测去除图像中的随机值脉冲噪声

The median filtering method and its improved methods is an effective approach to remove random-value impulse noise in images.However,most methods have the same shortcomings in finding the optimal threshold and the edges and over-smoothed textures structure of images.In the paper,we propose a novel method based on the geometric structure detection to remove random-value impulse noise from images.First,the histogram of a noisy image is used to estimate the noise ratio.Next,the two thresholds are adaptively determined from the noise ratio and the histogram of the detail image.Utilizing these two thresholds,all pixels in the detail image are divided into three sets:'uncorrupted pixels','undetermined pixels' and 'noise pixels'.The set of 'undetermined pixels' is often composed of pixels in edges and textures as well as noise pixels.Finally,the geometric structure detection is proposed to distinguish 'undetermined pixels'.Based on types of each pixel,the result of the median filtering is modified using the detail image.The simulation results show that the proposed method can remove impulse noise while preserve the edge structure of the image.It is superior to the existing methods in performance.