課程信息
4.6
688 ratings
157 reviews
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....
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100% 在線課程

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建議:4 hours/week

完成時間大約為24 小時
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English

字幕:English

您將獲得的技能

Image ProcessingData CompressionMatlab
Globe

100% 在線課程

立即開始,按照自己的計劃學習。
Calendar

可靈活調整截止日期

根據您的日程表重置截止日期。
Clock

建議:4 hours/week

完成時間大約為24 小時
Comment Dots

English

字幕:English

教學大綱 - 您將從這門課程中學到什麼

1

章節
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完成時間為 2 小時

Introduction to Image and Video Processing

In this module we look at images and videos as 2-dimensional (2D) and 3-dimensional (3D) signals, and discuss their analog/digital dichotomy. We 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. ...
Reading
3 個視頻(共 67 分鐘), 5 個閱讀材料, 1 個測驗
Video3 個視頻
Image and Video Signals 18分鐘
Electromagnetic Spectrum 24分鐘
Reading5 個閱讀材料
Welcome Class!10分鐘
Grading Policy10分鐘
Further Reading10分鐘
About Us10分鐘
Download the slides10分鐘
Quiz1 個練習
Homework 116分鐘

2

章節
Clock
完成時間為 2 小時

Signals and Systems

In this module we 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. ...
Reading
5 個視頻(共 82 分鐘), 4 個閱讀材料, 1 個測驗
Video5 個視頻
Complex Exponential Signals 18分鐘
Linear Shift-Invariant Systems 15分鐘
2D Convolution 15分鐘
Filtering in the Spatial Domain 13分鐘
Reading4 個閱讀材料
MATLAB10分鐘
Use of MATLAB for Programming Assignments10分鐘
In This Module... 10分鐘
Download the slides10分鐘
Quiz1 個練習
Homework 216分鐘

3

章節
Clock
完成時間為 2 小時

Fourier Transform and Sampling

In this module we look at 2D signals in the frequency domain. Topics include: 2D Fourier transform, sampling, discrete Fourier transform, and filtering in the frequency domain....
Reading
5 個視頻(共 92 分鐘), 2 個閱讀材料, 1 個測驗
Video5 個視頻
Sampling 22分鐘
Discrete Fourier Transform 16分鐘
Filtering in the Frequency Domain 13分鐘
Change of Sampling Rate 14分鐘
Reading2 個閱讀材料
In this Module...10分鐘
Download the slides10分鐘
Quiz1 個練習
Homework 316分鐘

4

章節
Clock
完成時間為 3 小時

Motion Estimation

In this module we 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...
Reading
5 個視頻(共 119 分鐘), 2 個閱讀材料, 1 個測驗
Video5 個視頻
Phase Correlation 9分鐘
Block Matching33分鐘
Spatio-Temporal Gradient Methods 23分鐘
Fundamentals of Color Image Processing31分鐘
Reading2 個閱讀材料
In This Module...10分鐘
Download the slides10分鐘
Quiz1 個練習
Homework 418分鐘
4.6
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Briefcase

83%

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創建者 SSJul 18th 2018

Very informative and comprehensive course in image processing. Many examples are presented throughout the course, which make the content tangible and help to better sink-in the material.

創建者 DKNov 4th 2017

This course is very beautifully designed to instill in your mind the concepts of Image and Video processing along with the graded quizzes to check how much actually you learned.

講師

Aggelos K. Katsaggelos

Joseph Cummings Professor
Department of Electrical Engineering and Computer Science

關於 Northwestern University

Northwestern University is a private research and teaching university with campuses in Evanston and Chicago, Illinois, and Doha, Qatar. Northwestern combines innovative teaching and pioneering research in a highly collaborative environment that transcends traditional academic boundaries. ...

常見問題

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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