数字图像处理与应用
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spContent=深刻理解图像处理原理,生动展现图像处理过程,灵活应用图像处理方法
—— 课程团队
课程概述

  图像和视频是人类记录、表达和传递外部世界的重要视觉载体,也是感知外部世界的视觉基础,图像处理是实现物联网、机器视觉和人工智能等相关应用的基本支撑技术。

  本课程将从如下八个方面来讲授图像处理的一些基本概念,方法与技术:

   1)图像表征(依据图像基信号是否基于数据驱动,介绍图像处理中经典的傅里叶变换,离散余弦变换和基于数据驱动的主元分析法,生动展现同一幅图像在不同变换下的形式)

   2)运动估计(分别介绍像素级别的光流法和图像块级别的块匹配算法原理,以及它们应用差异之所在)

   3)图像与视频压缩技术(分别介绍包括静态数字图像压缩标准JPEG和视频压缩MPEG原理)

   4)图像半色调技术(介绍包括最简单的阈值方法,用于印刷业的聚合型抖动模板和分散型抖动模板,误差传播法等)

   5)图像滤波技术(介绍图像中常见的噪声类型,传统图像滤波,如中值滤波和高斯滤波等,以及最近出现针对纹理的滤波方法)

   6)图像插值与超分辨率技术(介绍包括传统图像插值方法,和基于图像自相似图像超分辨率技术等)

   7)图像边缘检测与分割技术(介绍包括Canny算子,mean-shift图像色彩分割方法等)

   8)视频目标跟踪技术(介绍目前较热门的Discriminative Correlation Filter(DCF)的目标跟踪技术原理)。

在授课过程中我们通过理论与实践相结合方式,以及课后大量文献阅读来加深对图像处理基本概念和理论的理解;通过实例来分析比较不同图像处理方法的优缺点;通过提出问题来引导学生独立深入思考。

授课目标

课程的目标是通过学习,能让学员掌握图像处理与计算机视觉中一些基本概念,基本研究思路和方法等,从而帮助他们展开相关领域后续深入的研究工作,和开发相关应用系统等。

课程大纲
预备知识

线性代数,信号与系统,高等数学,统计概率论等。

证书要求

图像处理是一门应用性很强的课程,学员不应该只是弄明白图像处理的原理和方法,还要有能把图像处理中的方法实现出来的能力。完成所有课程的学习;能独立依照参考文献中所描述的方法用代码方式实现一种图像处理方法。

参考资料

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