平滑区域梯度保真的图像降噪方法

Denoising Method with Gradient Fidelity Term on Smoothing Region

基于有界变差的图像去噪模型在去除噪声的同时会产生"阶梯效应",在模型中耦合梯度保真项能够有效地抑制"阶梯效应",但全局梯度保真却导致图像的边缘模糊。新模型讨论了平滑区域的判定方法,在此基础上给出了基于平滑区域梯度保真的去噪模型和两种修正方法。新的去噪方法在去除图像噪声的同时压低了"阶梯效应",且能够很好地保留图像的边缘。数值实验验证了所提模型的效果。

Image denoising based on total variation may cause ＇staircase effect＇ while the noise is removed.Using the coupled gradient fidelity term can effectively restrain ＇staircase effect＇,but it makes edges obscured.This paper discussed the the way to detect smooth regions of an image.And three denoising methods with gradient fidelity term on smoothing region were proposed.Our methods can not only improve the denoising performance significantly,but also overcome ＇staircase effect＇ and preserve the edges.Numerical experiments demonstrate our models are efficiency.