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Fundamentals of Digital Image and Video Processing

Approx. 36 hours to complete

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Course Summary

The Digital Marketing Specialization is a comprehensive course that covers the basics of digital marketing, including content creation, social media marketing, and analytics.

Key Learning Points

Learn how to create effective digital marketing campaigns
Develop a strong understanding of social media marketing
Gain knowledge of analytics and data-driven decision making

Learning Outcomes

Develop a comprehensive digital marketing strategy
Create engaging content for various platforms
Use data to make informed decisions

Prerequisites or good to have knowledge before taking this course

Basic knowledge of marketing principles
Good communication skills
Access to a computer and internet connection

Course Difficulty Level

Beginner to Intermediate

Course Format

Online self-paced
Video lectures
Hands-on projects

Similar Courses

Social Media Marketing
Digital Marketing
Marketing in a Digital World

Related Education Paths

Notable People in This Field

Founder of Neil Patel Digital
CEO of VaynerMedia

Related Books

Description

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.

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. The ability to process image and video signals is therefore an incredibly important skill to master for engineering/science students, software developers, and practicing scientists. Digital image and video processing continues to enable the multimedia technology revolution we are experiencing today. Some important examples of image and video processing include the removal of degradations images suffer during acquisition (e.g., removing blur from a picture of a fast moving car), and the compression and transmission of images and videos (if you watch videos online, or share photos via a social media website, you use this everyday!), for economical storage and efficient transmission. This course will cover the fundamentals of image and video processing. We 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. We 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.

Outline

Introduction to Image and Video Processing
Analog v.s. Digital Signals
Image and Video Signals
Electromagnetic Spectrum
Welcome Class!
Grading Policy
Further Reading
About Us
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Homework 1

Signals and Systems
2D and 3D Discrete Signals
Complex Exponential Signals
Linear Shift-Invariant Systems
2D Convolution
Filtering in the Spatial Domain
MATLAB
Use of MATLAB for Programming Assignments
In This Module...
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Homework 2

Fourier Transform and Sampling
2D Fourier Transform
Sampling
Discrete Fourier Transform
Filtering in the Frequency Domain
Change of Sampling Rate
In this Module...
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Homework 3

Motion Estimation
Applications of Motion Estimation
Phase Correlation
Block Matching
Spatio-Temporal Gradient Methods
Fundamentals of Color Image Processing
In This Module...
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Homework 4

Image Enhancement
Introduction
Point-wise Intensity Transformations
Histogram Processing
Linear Noise Smoothing
Non-linear Noise Smoothing
Sharpening
Homomorhpic Filtering
Pseudo Coloring
Video Enhancement
In This Module...
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Homework 5

Image Recovery: Part 1
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
In This Module...
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Homework 6

Image Recovery : Part 2
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 Applications
In This Module...
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Homework 7

Lossless Compression
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
In This Module...
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Homework 8

Image Compression
Scalar Quantization
Vector Quantization
Differential Pulse-Code Modulation
Fractal Image Compression
Transform Coding
JPEG
Subband Image Compression
In This Module...
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Homework 9

Video Compression
Motion-Compensated Hybrid Video Encoding
On Video Compression Standards
H.261, H.263, MPEG-1 and MPEG-2
MPEG-4
H.264
H.265
In This Module...
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Homework 10

Image and Video Segmentation
Methods Based on Intensity Discontinuity
Methods Based on Intensity Similarity
Watersheds and K-Means Algorithms
Advanced Methods
In This Module...
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Homework 11

Sparsity
Introduction
Sparsity-Promoting Norms
Matching Pursuit
Smooth Reformulations
Applications
In This Module...
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Homework 12

Summary of User Reviews

The Digital Marketing course on Coursera has received positive reviews from users. They appreciated the course for its comprehensive coverage of digital marketing strategies and techniques. Overall, the course has been highly recommended by users.

Key Aspect Users Liked About This Course

The course provides a comprehensive coverage of digital marketing strategies and techniques.

Pros from User Reviews

The course is well-structured and easy to follow
The instructors are knowledgeable and experienced in the field
The assignments and projects are practical and relevant to real-world scenarios
The course provides a good foundation for those new to digital marketing
The course provides valuable insights into current digital marketing trends

Cons from User Reviews

Some users found the course too basic
Some users felt that the course could have been more interactive
Some users experienced technical difficulties with the course platform
Some users felt that the course lacked depth in certain areas
Some users felt that the course could have provided more case studies

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