Coursera platform offers, in cooperation with Northwestern University, a free online course: Fundamentals of Digital Image and Video Processing. In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests.
About The Fundamentals of Digital Image and Video Processing Course
Digital images and videos are everywhere these days – in thousands of scientific (e.g., astronomical, bio-medical), consumer, industrial, and artistic applications. Moreover they come in a wide range of the electromagnetic spectrum – from visible light and infrared to gamma rays and beyond.
This course will cover the fundamentals of image and video processing. You will provide a mathematical framework to describe and analyze images and videos as two- and three-dimensional signals in the spatial, spatio-temporal, and frequency domains.
In this class not only will you learn the theory behind fundamental processing tasks including image/video enhancement, recovery, and compression – but you will also learn how to perform these key processing tasks in practice using state-of-the-art techniques and tools.
They will introduce and use a wide variety of such tools – from optimization toolboxes to statistical techniques. Emphasis on the special role sparsity plays in modern image and video processing will also be given. In all cases, example images and videos pertaining to specific application domains will be utilized.
| The course is designed for | Beginner level. |
| Offered by | Coursera platform in cooperation with Northwestern University. |
| Course duration | 36 hours. |
| Price | Free of charge. |
| Certificate upon Completion | Available with the paid version. |
| Course language | English (Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish). |
| Already enrolled | 114,883 students. |
| Course Rating | 4,6/5. |
Course Syllabus
What you will learn from this course:
- Introduction to Image and Video Processing
In this module you look at images and videos as 2-dimensional (2D) and 3-dimensional (3D) signals, and discuss their analog/digital dichotomy. You will also see how the characteristics of an image changes depending on its placement over the electromagnetic spectrum, and how this knowledge can be leveraged in several applications.
- Signals and Systems
In this module you introduce the fundamentals of 2D signals and systems. Topics include complex exponential signals, linear space-invariant systems, 2D convolution, and filtering in the spatial domain.
- Fourier Transform and Sampling
In this module you look at 2D signals in the frequency domain. Topics include: 2D Fourier transform, sampling, discrete Fourier transform, and filtering in the frequency domain.
- Motion Estimation
In this module you cover two important topics, motion estimation and color representation and processing. Topics include: applications of motion estimation, phase correlation, block matching, spatio-temporal gradient methods, and fundamentals of color image processing
- Image Enhancement
In this module you cover the important topic of image and video enhancement, i.e., the problem of improving the appearance or usefulness of an image or video. Topics include: point-wise intensity transformation, histogram processing, linear and non-linear noise smoothing, sharpening, homomorphic filtering, pseudo-coloring, and video enhancement.
- Enhancement
In this module you study the problem of image and video recovery. Topics include: introduction to image and video recovery, image restoration, matrix-vector notation for images, inverse filtering, constrained least squares (CLS), set-theoretic restoration approaches, iterative restoration algorithms, and spatially adaptive algorithms.
- Image Recovery : Part 2
In this module you look at the problem of image and video recovery from a stochastic perspective. Topics include: Wiener restoration filter, Wiener noise smoothing filter, maximum likelihood and maximum a posteriori estimation, and Bayesian restoration algorithms.
How to enroll in Fundamentals of Digital Image and Video Processing course for free
Check the course official website and click on “Enroll For Free”. An enrollment box will pop up for you. Here you have two options, you can either join the paid version of the course by clicking on “Purchase Course ”, or you can view all course lessons for free by clicking on “Full Course, No Certificate”.
After clicking on “Full Course, No Certificate”, you can click on “Continue” to start your course for free!
If you are unable to pay and want a certificate, you can apply to Coursera for Financial aid.
The course official website
You can start the course following this link:
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