- Level Foundation
- المدة 36 ساعات hours
- الطبع بواسطة Northwestern University
-
Offered by
عن
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.الوحدات
Course Overview
4
Readings
- Welcome Class!
- Grading Policy
- Further Reading
- About Us
Introduction to Image and Video Processing
3
Videos
- Analog v.s. Digital Signals
- Image and Video Signals
- Electromagnetic Spectrum
1
Readings
- Download the slides
Test Your Knowledge
1
Assignment
- Homework 1
MATLAB
2
Readings
- MATLAB
- Use of MATLAB for Programming Assignments
Signals and Systems
5
Videos
- 2D and 3D Discrete Signals
- Complex Exponential Signals
- Linear Shift-Invariant Systems
- 2D Convolution
- Filtering in the Spatial Domain
2
Readings
- In This Module...
- Download the slides
Test Your Knowledge
1
Assignment
- Homework 2
Fourier Transform and Sampling
5
Videos
- 2D Fourier Transform
- Sampling
- Discrete Fourier Transform
- Filtering in the Frequency Domain
- Change of Sampling Rate
2
Readings
- In this Module...
- Download the slides
Test Your Knowledge
1
Assignment
- Homework 3
Motion Estimation
5
Videos
- Applications of Motion Estimation
- Phase Correlation
- Block Matching
- Spatio-Temporal Gradient Methods
- Fundamentals of Color Image Processing
2
Readings
- In This Module...
- Download the slides
Test Your Knowledge
1
Assignment
- Homework 4
Image Enhancement
9
Videos
- Introduction
- Point-wise Intensity Transformations
- Histogram Processing
- Linear Noise Smoothing
- Non-linear Noise Smoothing
- Sharpening
- Homomorhpic Filtering
- Pseudo Coloring
- Video Enhancement
2
Readings
- In This Module...
- Download the slides
Test Your Knowledge
1
Assignment
- Homework 5
Image Recovery
9
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
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 6
Image Recovery
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 Applications
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 7
Lossless Compression
8
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
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 8
Image Compression
7
Videos
- Scalar Quantization
- Vector Quantization
- Differential Pulse-Code Modulation
- Fractal Image Compression
- Transform Coding
- JPEG
- Subband Image Compression
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 9
Video Compression
6
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
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 10
Image and Video Segmentation
4
Videos
- Methods Based on Intensity Discontinuity
- Methods Based on Intensity Similarity
- Watersheds and K-Means Algorithms
- Advanced Methods
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 11
Sparsity
5
Videos
- Introduction
- Sparsity-Promoting Norms
- Matching Pursuit
- Smooth Reformulations
- Applications
2
Readings
- In This Module...
- Download the Slides
Test Your Knowledge
1
Assignment
- Homework 12
Auto Summary
Unlock the fascinating world of Digital Image and Video Processing with this comprehensive course, designed for those diving into Science & Engineering. Guided by expert instructors, this course delves into the fundamental principles and tools necessary for processing images and videos, enabling learners to solve practical problems in various fields, from commercial applications to scientific research. Digital imagery is integral to numerous applications, ranging from astronomy and bio-medicine to consumer technology and the arts. This course equips you with the skills to enhance, recover, and compress digital images and videos, essential for efficient storage and transmission. You'll learn to handle signals across the electromagnetic spectrum, including visible light, infrared, and gamma rays. Over the duration of approximately 36 hours, you'll gain a robust mathematical framework to analyze images and videos as multi-dimensional signals. The curriculum covers vital processing tasks such as image/video enhancement and compression, utilizing cutting-edge techniques and tools, including optimization toolboxes and statistical methods. Special emphasis is placed on the role of sparsity in modern image and video processing, with practical examples from various application domains. Available through Coursera, the course offers a foundational-level learning experience with flexible subscription options. Perfect for engineering and science students, software developers, and practicing scientists eager to master an important and evolving skill set in the multimedia technology revolution.
Aggelos K. Katsaggelos