Adaptive image denoising model based on total variation
Peng Qi-cong · Guangdian gongcheng · 2006
An adaptive image denoising model based on Total Variation (TV) is proposed by analyzing the three important denoising models: harmonical model, TV model and generalized TV model, in the variational image restoration. Firstly, the convolution of the Gaussian filter and the noisy image can remove a small portion of the noise so it is less likely to be detected as an edge, and then we can adaptively select the most appropriate denoising scheme based on the gradient information of each pixel. Numerical experiments show that the proposed method can remove the noise while preserving significant image details. At high noise level,the method achieves at least 1.0dB gain over other variational denoising methods for Peak Signal-Noise Ratio (PSNR) measurement.