An adaptive TV model for image denoising
Gao Leifu, Chao Li · 2013
By analyzing three important denoising models: the harmonical model, the TV (total variation) model and the generalized TV model, we have proposed an adaptive one which is named `adaptive TV image denoising model'. On the basis of SNR of noisy images, this model can pretreat them with Gaussian filter, so as to overcome the staircase effect in the TV model. Then by utilizing the gradient information of every pixel point of the image, we can adaptively select the most appropriate denoising scheme. The results of numerical experiments show that this method can preserve significant image details while removing the noise. Compared with other variational denoising methods, especially at high noise levels, the method achieves at least about 1.0dB gain for Peak Signal to the Noise Ratio (as PSNR for short) measurement.