An Adaptive Hybird Denoising Algorithm For Image Based On Thought Of Pixels Classifying

Images are often corrupted in acquisition and transmission by various kind of noise,in cluding additive Gaussian white noise,impulse noise,multiplicative noise,etc. To improve the visual quality of the images and to faciliate succeeding procedure (edge detection etc),many denoising approaches have been proposed,such as the median filtering algorithm for impulse noise and the neighborhood denoising approch for additive Gaussian white noise. However,current approaches concentrate on the removal of noise but lack the preservation of edges in images, causing the outcome images blurred.The edges often contain the details of images and the destruction of image details will affect follow image recognition. In this dissertation,we analyze some classic algorithms for additive Gaussian white noise and salt-pepper noise and propose an adaptive hybird denosing algorithm for image based on thought of pixels classifying.In an image,variant of the plain area is less than the edge area and implus noise area. We classify centre pixels of different areas according to the value of the variant and use different approachs for denoising. For impulse noise pixels,we will use area median filter. For edge pixels,we will use the weighted linear filter in pixels of similar grey level. For other pixels,we will use different parameter 3×3 masks of Gaussian smoothing,and we can get the parameters of the mask through the linear function so that acquiring the adaptive effect.The approach taken in this paper have considered the image edge details preserving and the whole denoising,after sorting and details preserving by using the thoughts of classifying,and then the similar pixels in same sort will be smoothed. Using this method to differ the edge pixels from un-edge pixels so that the information of image details can be preserved as possible as we can.The simulation based on this algorithm had been carry out in this paper,and compared with same tradional filtering algorithms in subjective and objective aspect. From the result,we can conclude that the algorithm taken in this paper precede the common filter algorithm in denosing and edge-preserving.