Infrared Image Denoising Based on Wavelet Transform

Wavelet-domain infrared image denoising based on a new kind of thresholding function is proposed.The proposed thresholding function is simple and continuous.It overcomes the discontinuous shortcoming of the hard thresholding function and the disadvantage of soft thresholding function which is the invariable dispersion between the estimated wavelet coefficients and the wavelet coefficients contaminated by noise.At the same time,the clustering characteristics of wavelet coefficients are utilized effectively in new function.That is,the neighboring wavelet coefficients are incorporated into the estimation of wavelet coefficients.Simulation results show that the proposed denoising algorithm owns better visual effect and PSNR performance than many exiting thresholding methods and Matlab-wiener 2 method.