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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The certificate course on Fundamentals Of Digital Image And Video Processing by Coursera teaches the basic tools and principles of video and image processing and the best way of applying them in solving problems of scientific and commercial interests. Today digital images are used everywhere, in artistic applications, Industrial and consumer applications, in Scientific (bio-medical, astronomical, etc) applications.

The Fundamentals Of Digital Image And Video Processing Course covers the fundamentals involved in video and image processing. It provides the mathematical framework required to analyze and describe videos and images as 2D and 3D signals in Spatio-temporal, Spatial and frequency domain. The programme teaches not just the image enhancement but also the fundamentals, the theory involved, compression, and recovery.

The course teaches uses of a wide range of tools like statistical techniques as well as the use of optimisation toolboxes. The key role that Sparsity plays in modern-day video and image processing is also thoroughly explained. Candidates who wish to pursue a career in image processing of any of the scientific fields of its application must take this course to advance themselves in pace with the changing technology and research.

The Highlights

Flexible deadlines
Self-paced
Approx. 35 hours of online learning
Certificate of completion
Video content and reading material are available for download.
Class videos are provided with English subtitles.
Offered by Northwestern

Programme Offerings

assignments
Online Classes
self paced course

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 2381	yes	Coursera

Coursera offers this programming Fundamentals of Digital Image and Video Processing Course for free of cost.

Type of Programme	Amount
Full Course, No Certificate	Free
Purchase Course	Rs. 2,381

Eligibility Criteria

Certification Qualifying Details

The certificate on Fundamentals of Digital Image and Video Processing awards a shareable certificate to all the candidates who complete the entire course and submit graded assignments and quizzes satisfactorily.

What you will learn

Knowledge of MATLAB

Candidates completing the Fundamentals of Digital Image and Video Processing programme on Coursera will develop an understanding of the following:

Working knowledge of image processing and video processing from signals and systems using the fundamentals and theories learned in the course.
Developing an understanding and application of motion estimation and color representation and processing for phase correlation and block matching etc.
Applying the knowledge for image enhancement and image recovery in various scenarios and understanding what practice best suits in different situations.
The best practices in the field used to face challenges in video and image compression and segmentation.
Applying the knowledge of all the tools and experiences gained from the course as well as graded assignments and quizzes for utilizing it to their advantage in solving complex problems arising in the industry.

Who it is for

Software DeveloperComputer Systems EngineerScientist

The Fundamentals of Digital Image and Video Processing Programme is an extremely relevant course suits, multi-discipline candidates.

The course can be of help to the following:

For artists who use video and image processing to enhance, recover, transform and compress videos and image files almost every day.
Medical Professionals in the field of video and image processing representing the inside of the body for better analyzing and determining any health complications and the need for medical interventions if need be.
Candidates working in the field of space and astronomy who utilise the signal and systems to process video and image files of a large quantum.
Industrial or consumer professionals who are learning to better their skills of image processing for commercial applications.

Admission Details

To take admission in this Fundamentals of Digital Image and Video Processing programme, Candidates can follow these simple steps to register:

Step 1: Visit the course information page on Coursera and click ‘Enrol’

Step 2: Register for an account with Coursera with an email id or a Google / Facebook account. If you are an existing account holder you can just simply log in.

Step 3: Choose how to take the course. To buy the paid-up course with a certificate, enrol and pay the course fee. Candidates can also get to audit the course for free. However, the ‘free audit’ mode does not provide certification.

Step 4: You can also choose a free 7-day trial of Coursera plus, this is a paid version of Coursera. The trial is a great way to experience the benefits before buying.

Step 5: The candidates who buy the course will next be taken to pay the course fee. Choose from any of the payment modes available.

Step 6: After the fee payment / enrolling for the free audit course, candidates will get access to the lectures and relevant material.

Step 7: Candidates can download video lectures and course material to watch later. The deadlines can also be reset and they are flexible.

The Syllabus

Videos

Electromagnetic Spectrum
Video and Image Signals
Analog v.s. Digital Signals

Readings

Welcome Class!
Grading Policy
Further Reading
About Us
Download the slides

Practice Exercise

Homework 1

Videos

2D and 3D Discrete Signals
Complex Exponential Signals
Linear Shift-Invariant Systems
2D Convolution
Filtering in the Spatial Domain

Readings

MATLAB
Use of MATLAB for Programming Assignments
In This Module...
Download the slides

Practice Exercise

Homework 2

Videos

2D Fourier Transform
Sampling
Discrete Fourier Transform
Filtering in the Frequency Domain
Change of Sampling Rate

Readings

In this Module...
Download the slides

Practice Exercise

Homework 3

Videos

Applications of Motion Estimation
Phase Correlation
Block Matching
Spatio-Temporal Gradient Methods
Fundamentals of Color Image Processing

Readings

In This Module...
Download the slides

Practice Exercise

Homework 4

Videos

Introduction
Point-wise Intensity Transformations
Histogram Processing
Linear Noise Smoothing
Non-linear Noise Smoothing
Sharpening
Homomorphic Filtering
Pseudo Coloring
Video Enhancement

Readings

In This Module...
Download the slides

Practice Exercise

Homework 5

Videos

Examples of Image and Video Recovery
Image Restoration
Matrix-Vector Notation for Images
Inverse Filtering
Constrained Least Squares
Set-Theoretic Restoration Approaches
Iterative Restoration Algorithms
Iterative Least-Squares and Constrained Least-Squares
Spatially Adaptive Algorithms

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 6

Videos

Wiener Restoration Filter
Wiener v.s. Constrained Least-Squares Restoration Filter
Wiener Noise Smoothing Filter
Maximum Likelihood and Maximum A Posteriori Estimation
Bayesian Restoration Algorithms
Other Restoration Application
Wiener v.s. Constrained Least-Squares Restoration Filter
Wiener Noise Smoothing Filter
Maximum Likelihood and Maximum A Posteriori Estimation
Bayesian Restoration Algorithms
Other Restoration Applications

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 7

Videos

Introduction
Elements of Information Theory - Part I
Elements of Information Theory - Part II
Huffman Coding
Run-Length Coding and Fax
Arithmetic Coding
Dictionary Techniques
Predictive Coding

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 8

Videos

Scalar Quantization
Vector Quantization
Differential Pulse-Code Modulation
Fractal Image Compression
Transform Coding
JPEG
Subband Image Compression

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 9

Videos

Motion-Compensated Hybrid Video Encoding
On Video Compression Standards
H.261, H.263, MPEG-1 and MPEG-2
MPEG-4
H.264
H.265

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 10

Videos

Methods Based on Intensity Discontinuity
Methods Based on Intensity Similarity
Watersheds and K-Means Algorithms
Advanced Methods

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 11

Videos

Introduction
Sparsity-Promoting Norms
Matching Pursuit
Smooth Reformulations
Applications

Readings

In This Module...
Download the Slides

Practice Exercise

Homework 12

Instructors

Northwestern University, Evanston Frequently Asked Questions (FAQ's)

1: How can I resolve any doubts during the course?

Coursera has a dedicated student forum. Peers attending the same course can interact and discuss any doubts and queries. Candidates can ask their doubts at any time and get a quick peer-reviewed answer. Coursera offers email support to students.

2: What are the benefits of opting for the course?

Coursera courses are taught by industry experts from the leading universities in the world. They specialize in respective subjects and offer practical solutions and insights into the challenges encountered in the field. The courses are curated for all levels of learning.

3: Do I need to be present on campus for classes?

This course on the Fundamentals of Digital Image and Video Processing is a completely online course. Candidates can download/ view their lectures at their own suitable time and pace through their phones and laptops. The course does not need any campus/classroom visits.

4: Do I need to cover the course content in any particular order?

Yes. The classes at the beginning impart the necessary orientation, introduction and are the basic building blocks of later classes. If candidates start classes without the basics, it can disturb the flow of learning.

5: How long will it take to complete the programme?

The course has 36 hours of learning available for candidates. However, it is totally up to the individual to pace the course and they can take as much time as they wish.

6: When do you get access to the course material?

The course material will be made available to all candidates on paying fee / enrolling for the free audit mode of the course. They will get access to reading materials, videos, and assignment files.