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.
Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital
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Habilidades que você terá
Programa - O que você aprenderá com este curso
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.
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. Also will describe what is done in the Mars expedition.
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 simple and still popular approaches. We will also include non-local means, a more modern technique that still uses classical tools.
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 and powerful classical tools.
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 interpretation, and will learn why this is important, e.g., in medical imaging and object recognition.
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 “advanced” unit and smoothly follows from the previous one. Students will learn very modern tools, widely used today, and will contrast with units 3,4 to illustrate how significantly more advanced mathematical tools are also very useful in image and video analysis. We will connect some of these advanced tools with classical ones, e.g., average with heat flow and median with anisotropic diffusion. This will help to provide unified views to the students.
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 illustrate how the same problem can be approached from multiple mathematical angles. We will connect this with Shanon’s work providing yet another angle. If you watched the lectures on PDEs you will have more mathematical background, but you will enjoy this unit and learn without it as well.
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 video processing. This is the last formal unit of the course.
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 in these exciting applications, from the acquisition to the analysis.
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Principais avaliações do Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital
I god certified from Duke University through Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital\n\nAmazing with Coursera platform really Got Experienced from this subject
This course was really great in explaining the Image and video processing basics. I do not have an extensive maths background, but was still able to grasp the concepts. Thanks.
Instrutores
Guillermo Sapiro
ProfessorSobre Universidade Duke
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao adquirir o Certificado?
Quando você adquire o Certificado, ganha acesso a todo o material do curso, incluindo avaliações com nota atribuída. Após concluir o curso, seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
Qual é a política de reembolso?
Existe algum auxílio financeiro disponível?
Will I have fun?
Yes
Do I need strong math background for this class?
Some but not much. If you have you will get a more in depth understanding. We hope you know linear algebra for example. Again, some concepts you will grasp even without strong mathematical background. Some will consider this an advanced undergrad class.
Who uses image processing in industry?
Who doesn't?
Do I need any programming skills?
We suggest some optional (not graded) programming exercises. The forums discuss them a lot and this is fun.
Will I receive a transcript from Duke University for completing this course?
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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