Image De-Noising using Wavelets- A Clustering Based Method

In the process of image acquisition and transmission, noise is always contained inevitably. So it is necessary to image denoising processing to improve the quality of image. Generally speaking, each algorithm has some filtering and threshold parameters. Taking variety kinds of images into account, it is a key problem of how to set these parameters in de-noising algorithms under different conditions to achieve better performance. There are many algorithms for the determination of the parameters, and each of them has its application field. Because the wavelet transform has good performance, therefore, it has been widely applied as a kind of signal and image processing tools. In this paper, wavelet transform is used in the image de-noising and we propose a new algorithm similar to k-means clustering in machine learning which gives better performance and Experimental results show the validity of the new algorithm. Keywordsimage de-noising, wavelet transform, k-means clustering, mean filter, median filter