一种改进的双项自适应总体变差去噪模型

研究经典总体变差去噪模型及其改进的自适应去噪模型，提出一种基于预处理图像局部信息的双项自适应模型。利用空间自适应保真项缓解二阶非线性滤波对细节的过度平滑，通过自适应正则化项减少阶梯效应，使数值更稳定和收敛。实验结果表明，与原方法相比，改进方法具有更好的鲁棒性，在噪声较高的情况下仍能取得较好的去噪效果。

An Improved Double-term Adaptive Total Variation De-noising Model

On the base of the classic total variation de-noising model and its improved models, this paper proposes an improved double-entry adaptive Total Variation(TV) model based on local information of pre-made images. An adaptive spatial fidelity term is intended to ease the smoothing effect by the second-order nonlinear filtering over the details. An adaptive regularization term is to further reduce the staircase effect, also to achieve a more stable and convergence value. Experimental results show that the improved method still can achieve better results in high noise. Compared with the original method, it has better noise robustness.