In this paper, we introduce two novel total variation models to deal with speckle noise in ultrasound image in order to retain the fine details more effectively and to improve the speed of energy diffusion during the process. Firstly, two new convex functions are introduced as regularization term in the adaptive total variation model, and then, the diffusion performances of Hypersurface Total Variation (HYPTV) model and Logarithmic Total Variation (LOGTV) model are analyzed mathematically through the physical characteristics of local coordinates. We have shown that the larger positive parameter in the model is set, the greater energy diffusion speed appears to be, but it will cause the image to be too smooth that required adequate attention. Numerical experimental results show that our proposed LOGTV model for speckle noise removal is superior to traditional models, not only in visual effect but also in quantitative measures.

中文翻译：

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具有新的正则化设置的能量模型去除斑点噪声

在本文中，我们引入了两个新颖的总变化模型来处理超声图像中的斑点噪声，以便更有效地保留细节并提高过程中的能量扩散速度。首先，在自适应总变化模型中引入了两个新的凸函数作为正则项，然后通过局部坐标的物理特征对超曲面总变化（HYPTV）模型和对数总变化（LOGTV）模型的扩散性能进行了数学分析。 。我们已经表明，在模型中设置较大的正参数时，似乎会出现较大的能量扩散速度，但是这将导致图像过于平滑，需要足够的注意。