深度学习与图像复原

第1 章 基于传统机器学习的图像复原方法 ............................................................. 11.1 图像去噪 ···············································································11.1.1 图像去噪任务简介···························································11.1.2 基于传统机器学习的图像去噪方法 ·····································11.2 图像超分辨率 ·········································································91.2.1 图像超分辨率任务简介 ····················································91.2.2 基于传统机器学习的图像超分辨率方法 ·······························91.3 图像去水印 ·········································································.151.3.1 图像去水印任务简介 ····················································.151.3.2 基于传统机器学习的图像去水印方法 ·······························.151.4 本章小结 ············································································.19参考文献 ···················································································.20第2 章 基于卷积神经网络的图像复原方法基础 ................................................... 242.1 卷积层 ···············································································.24第1 章 基于传统机器学习的图像复原方法 ............................................................. 1 1.1 图像去噪 ···············································································1 1.1.1 图像去噪任务简介···························································1 1.1.2 基于传统机器学习的图像去噪方法 ·····································1 1.2 图像超分辨率 ·········································································9 1.2.1 图像超分辨率任务简介 ····················································9 1.2.2 基于传统机器学习的图像超分辨率方法 ·······························9 1.3 图像去水印 ·········································································.15 1.3.1 图像去水印任务简介 ····················································.15 1.3.2 基于传统机器学习的图像去水印方法 ·······························.15 1.4 本章小结 ············································································.19 参考文献 ···················································································.20 第2 章 基于卷积神经网络的图像复原方法基础 ................................................... 24 2.1 卷积层 ···············································································.24 2.1.1 卷积操作 ····································································.26 2.1.2 感受野 ·······································································.29 2.1.3 多通道卷积和多卷积核卷积 ···········································.30 2.1.4 空洞卷积 ····································································.31 2.2 激活层 ···············································································.33 2.2.1 Sigmoid 激活函数 ·························································.33 2.2.2 Softmax 激活函数 ·························································.35 2.2.3 ReLU 激活函数 ···························································.36 2.2.4 Leaky ReLU 激活函数 ···················································.38 2.3 基于卷积神经网络的图像去噪方法 ···········································.39 2.3.1 研究背景 ····································································.39 2.3.2 网络结构 ····································································.40 2.3.3 实验结果 ····································································.42 2.3.4 研究意义 ····································································.47 2.4 基于卷积神经网络的图像超分辨率方法 ·····································.48 2.4.1 研究背景 ····································································.48 2.4.2 网络结构 ····································································.48 2.4.3 实验结果 ····································································.51 2.4.4 研究意义 ····································································.55 2.5 基于卷积神经网络的图像去水印方法 ········································.55 2.5.1 研究背景 ····································································.55 2.5.2 网络结构 ····································································.56 2.5.3 实验结果 ····································································.58 2.5.4 研究意义 ····································································.61 2.6 本章小结 ············································································.62 参考文献 ···················································································.62 第3 章 基于双路径卷积神经网络的图像去噪方法 ............................................... 69 3.1 引言 ··················································································.69 3.2 相关技术 ············································································.70 3.2.1 空洞卷积技术 ······························································.70 3.2.2 残差学习技术 ······························································.71 3.3 面向图像去噪的双路径卷积神经网络 ········································.72 3.3.1 网络结构 ····································································.72 3.3.2 损失函数 ····································································.74 3.3.3 重归一化技术、空洞卷积技术和残差学习技术的结合利用 ····.74 3.4 实验结果与分析 ···································································.76 3.4.1 实验设置 ····································································.77 3.4.2 关键技术的合理性和有效性验证 ·····································.79 3.4.3 灰度与彩色高斯噪声图像去噪 ········································.83 3.4.4 真实噪声图像去噪························································.87 3.4.5 去噪网络的复杂度及3