Image De-noising with Stationary Wavelet Transform

摘要

Wavelet de-noising attempts to remove the noise present in the image while preserving the main features of the image. The method is based on threshold estimation for each sub band of the wavelet decomposition of a noise contaminated image, by considering that the sub band coefficients have a generalized Gaussian distribution. The stationary wavelet transformation (SWT) has been used to transform the noisy image, as the main application of SWT is de-noising. We used a new threshold value which is based on the size of the data. The experiments has been conducted on various test images and compared the performance in terms of peak signal to noise ratio with the established threshold parameters.