Image and video processing: From Mars to Hollywood with a stop at the hospital

开始时间: 01/04/2016 持续时间: 9 weeks

所在平台: Coursera

课程类别: 数学

大学或机构: Duke University(杜克大学)

授课老师: Guillermo Sapiro



课程评论: 1 个评论

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What is image and video processing? Images and videos are everywhere, from those we take with our mobile devices and share with our friends to those that we receive from Mars and the ones we see in the movie theatre, without forgetting the whole ensemble of images of our bodies that are taken in hospital visits. Image and video processing is the art of working with such images and movies, from making it possible to store and transmit them to making those dark and blurry images look nice, as well as interpreting and analyzing the medical data and recognizing our friends’ faces in social pictures. This discipline is also fascinating because it uses tools from many areas of applied mathematics. In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.

The course will start with an introduction to the basics of image formation and the fundamental concepts that translate a physical scene into a digital image. We will then describe the underlying concepts of image compression, the enabling technology that makes it possible for images to be sent from Mars and videos to be stored in our mobile phones. We will cover the most fundamental tools in image enhancement, showing how simple tools can significantly improve images. Both geometric and non-geometric tools as well as spatial and non-spatial operations will be presented. Details on image segmentation will be provided, one of the most fundamental and useful problems in image processing. The above topics will be extended to color images and video. Once we have covered the fundamentals, which both provide the basis for modern image and video processing and serve many important applications until today, we will move into recent progress in the area, covering image inpainting (how to remove objects from images and video), image processing via sparse modeling and compressed sensing, geometric partial differential equations for image analysis, image processing for HIV and virus research, and image processing for neurosurgery and other medical applications.


Week 1- Introduction to Image and Video Processing: We will cover the fundamentals, including some elements of visual perception, sensing, sampling, and quantization.

Week 2- Image and Video Compression: We will learn the fundamental tools enabling us to receive images from Mars, to upload images to the web, and to store a lot of images and videos in our mobile phones.

Week 3- Spatial Processing: This week we will learn some of the most classical and fundamental tools that help us still today to make noisy, blurry, and dark images look much better.

Week 4- Image Restoration: When something is known or estimated about the degradation process, we can do much better, and in this week we will learn how.

Week 5- Image Segmentation: How do we split an image or video in its core components?

Week 6- Geometric PDEs: We will learn about the use of partial differential equations and geometric deformations for problems like image enhancement and object detection.

Week 7- Image and Video Inpainting: How to make objects disappear and other special effects.

Week 8- Sparse Modeling and Compressed Sensing: We will cover some of the most modern tools for image enhancement and image analysis.

Week 9- Medical Imaging: As an example of medical image analysis, we will illustrate examples and techniques in the areas of brain research and virus analysis.



freealbert 2013-10-31 20:55 0 票支持; 0 票反对

这门课定位应该是图像处理的入门课程, 内容很全面也很鲜活,从灰度,像素等的最基础的知识一直讲到如今在学术界大红大紫的稀疏表示。Slide和Demo演示都很赞,相信应该能激起很多人对图像处理的兴趣,K-SVD算法就是在他的课上搞明白的。 关于授课老师, Sapiro本人是图像处理的大牛, 光在IEEE上就有文章150余篇, 在PDE和小波方面都有很大的贡献.


In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.


图像 视频 视频处理 图像处理 图像和视频处理



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