Image Denoising Based on Wavelet Coefficients and Least Squares Support Vector Machine

The least squares support vector machine(LS-SVM) is a modified version of SVM,which simplifies the complexity of optimization problem of the SVM algorithm.In this paper,a wavelet-based image denoising using LS-SVM is proposed.According to the nature of the wavelet coefficients,the average of the neighborhood of wavelet coefficients as the feature vectors for training are selected.Then the noisy image pixels are divided into noise and non-noise pixels by the training LS-SVM classifier and noise processing.The experimental results show that,by using this method,a higher PSNR could be achieved,and a better donoising effective could be have.