MATLAB计算机视觉与深度学习实战-赠在线交流卡和本书源码

第 1 章 基于直方图优化的图像去雾技术 1
1.1 案例背景 ·········································································································· 1
1.2 理论基础 ·········································································································· 1
1.2.1 空域图像增强 ····························································································· 1
1.2.2 直方图均衡化 ····························································································· 2
1.3 程序实现 ·········································································································· 3
1.3.1 设计 GUI 界面 ···························································································· 4
1.3.2 全局直方图处理 ·························································································· 4
1.3.3 局部直方图处理 ·························································································· 7
1.3.4 Retinex 增强处理 ························································································· 9
1.4 延伸阅读 ········································································································ 13
1.5 参考文献 ········································································································ 13
第 2 章 基于 形态学的权重自适应图像去噪 14
2.1 案例背景 ········································································································ 14
2.2 理论基础 ········································································································ 15
2.2.1 图像去噪方法 ··························································································· 15
2.2.2 数学形态学原理 ························································································ 16
2.2.3 权重自适应的多结构形态学去噪 ··································································· 16
2.3 程序实现 ········································································································ 17
2.4 延伸阅读 ········································································································ 22
2.5 参考文献 ········································································································ 23
第 3 章 基于多尺度形态学提取眼前节组织 24
3.1 案例背景 ········································································································ 24
3.2 理论基础 ········································································································ 25
3.3 程序实现 ········································································································ 28
3.3.1 多尺度边缘 ······························································································ 28
3.3.2 主处理函数 ······························································································ 29
3.3.3 形态学处理 ······························································································ 31
3.4 延伸阅读 ········································································································ 33
3.5 参考文献 ········································································································ 33
第 4 章 基于 Hough 变化的答题卡识别 34
4.1 案例背景 ········································································································ 34
4.2 理论基础 ········································································································ 34
4.2.1 图像二值化 ······························································································ 35
4.2.2 倾斜校正 ································································································· 35
4.2.3 图像分割 ································································································· 38
4.3 程序实现 ········································································································ 40
4.4 延伸阅读 ········································································································ 51
4.5 参考文献 ········································································································ 51
第 5 章 基于阈值分割的车牌定位识别 52
5.1 案例背景 ·············