In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space. The course starts by looking at how the human visual system works and then teaches you about the engineering, mathematics, and computer science that makes digital images work. You will learn the basic algorithms used for adjusting images, explore JPEG and MPEG standards for encoding and compressing video images, and go on to learn about image segmentation, noise removal and filtering. Finally, we will end with image processing techniques used in medicine. This course consists of 7 basic modules and 2 bonus (non-graded) modules. There are optional MATLAB exercises; learners will have access to MATLAB Online for the course duration. Each module is independent, so you can follow your interests.
- Week 1 - Introduction to image and video processing
Learn what is image and video processing. Learn the very basic concepts of human perception needed for understanding image processing. Learn simple tools in signal processing needed to understand following units.
- Week 2 - Image and video compression
JPEG and MPEG are the most successful algorithms in the area, widely used by everybody in a daily basis, and the goal of this unit is to understand how they work. Also to understand why these techniques are important and why they are enabling technologies. Als...
- Week 3 - Spatial processing
Some of the most basic tools in image processing, like median filtering and histogram equalization, are still among the most powerful. We will describe these and provide a modern interpretation of these basic tools. Students will then become familiar with simp...
- Week 4 - Image restoration
The goal of this unit is to complement Unit 3 by adding prior information about the sources of degradation. Students will learn that if we know about the degradation process, we can do better. The objective of this unit is to complete the training with basic a...
- Week 5 - Image segmentation
Not all parts of the image are the same, and students will learn the basic techniques to partition an image, from simple threshold to more advanced graph cuts and active contours. This is the first unit where student will learn about image analysis and image i...
- Week 6 - Geometric PDEs
This is all optional material. It will help the students that are more mathematically oriented and want to better understand the math behind next unit's lectures. But you will be able to handle without it.The quiz is therefore practice only.This is the first “...
- Week 7 - Image and video inpainting
Students will get involved with a very exciting topic, since image and video inpainting is one of the most used tools in the movie industry. They will learn the problem, and also how they can approach it from multiple directions. This will also help to illustr...
- Week 8 - Sparse modeling and compressed sensing
Here the goal is to present one of the most modern tools in image and video processing, and students will learn something that is today at the top of active research. This will also help to illustrate the use of linear algebra and optimization in image and vid...
- Week 9 - Medical imaging
This is a bonus unit. Enjoy it. Image processing has been very successful in medical imaging, and we will use examples from HIV and brain research to illustrate the importance of image processing in solving societal problems. We will describe the basic tools i...
Electrical and Computer Engineering
Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.
Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.