An Adaptive Image Denoising Algorithm Based on Wavelet Transform and Independent Component Analysis

Independent Component Analysis(ICA) Is a kind of effective method for separating independent noise source. This paper proposed an improved Wavelet ICA filter, which could segregate the noise from Image. The suggested method using wavelet dimension reduction and normalizing the signal reduced the dimensionality through ICA that find independent noise characteristics and solve the problem of Non-orthogonality by using Morlet wavelet if necessary. We compared this algorithm with Principal Component Analysis (PCA) and FastICA by experiment to verify the effectiveness of the proposed method. The results show that the method proposed in this paper is much better than PCA and FastICA in image denoising.