...-06-21 10:51:04 阅读次数：50 损失函数 损失函数(loss function) = 误差部分(loss term) + 正则化部分(regularization term) 1.
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The energy function is composed of regularization term and matching term. The matching term reflects the disparity of the relevant point, the regularization term reflects the smoothness of the image.
匹配项反映了对应点的视差，正则项则是对初始视差图的优化平滑。
参考来源 - 基于CCD图像的三维重建技术研究与实现·2,447,543篇论文数据，部分数据来源于NoteExpress
The energy function is composed of regularization term and matching term.
在构造能量函数的时候，引入匹配项和正则项。
A deconvolution approach with an additive regularization term built around an minimal L1 norm is proposed.
文中在基于最小L1范数的加性调整条件下，提出了一种新的去卷积方法。
In this paper, these shortcomings of inverse diffusion model were considered and the variational model of image enhancement coupling high order regularization term was proposed.
针对以上问题，提出了一种引入高阶正则项约束的逆扩散变分图像增强模型。
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