Chinese Optics Letters, Vol. 5, Issue 11, 632 (2007)
Image denoising using least squares wavelet support vector machines
Guoping Zeng* and Ruizhen Zhao
- Institute of Information Science, Beijing Jiaotong University, Beijing 100044
We propose a new method for image denoising combining wavelet transform and support vector machines (SVMs). A new image filter operator based on the least squares wavelet support vector machines (LS-WSVMs) is presented. Noisy image can be denoised through this filter operator and wavelet thresholding technique. Experimental results show that the proposed method is better than the existing SVM regression with the Gaussian radial basis function (RBF) and polynomial RBF. Meanwhile, it can achieve better performance than other traditional methods such as the average filter and median filter.
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