Retour à Fondements de l'image numérique et du traitement des vidéos

4.6

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1,349 évaluations

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274 avis

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....

Mar 21, 2019

AMAZING COURSE.\n\nTAKES YOU THROUGH EVERY TOPIC IN IMAGE PROCESSING.\n\nTHIS COURSE GREATLY HELPED ME WITH UNIVERSITY STUDIES AS WELL,\n\nTHANK YOU NORTHWESTERN UNIVERSITY AND PROFESSOR AGGELOS K.

Oct 07, 2018

This course is much simpler and easier to understand for those who wanna get and set their goals towards the image engineering field. Really enjoy much doing this course. THank you everyone !!!

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par Bram M

•Oct 20, 2017

The course combines a relatively high mathematical level with a lack of depth. For people that understand the mathematics it won't go deep enough/not explain a lot of the things in depth. The depth fits better with someone that doesn't understand the mathematics, but they won't be able to follow the mathematics. In short, I don't understand who this course is meant for, definitely not for me. The level of the content seems to me like perhaps third year of a Bachelor's or undergrad degree. If you do not have some background in mathematics, don't take this course. It is way too easy to pass the quizzes. You just shouldn't be able to pass with 50%. Also, the presentations are often not very focused. Sometimes the teacher glosses over quite important things you need to really understand what's going on. However, sometimes a lot of time is spent explaining completely trivial things (at least they will be trivial to anyone that understands the rest of the course). I decided to also do a different course in this field, because I don't feel I learned that much here. I did a Physics bachelor's and master's degree and am already proficient in MATLAB. It took me about 3-4 hours per week to learn the content and make the quiz in the first 8 weeks. If you want to really understand the content, you will have to find sources outside coursera as well. The last 4 weeks I got too annoyed with the presentations glossing over everything that I went through it more quickly. I do not recommend following this course.

par Jonathan B

•Nov 03, 2018

This class is WAY too theoretical, I took it hoping to have emphasis on matlab but I was very disappointed. The lectures didn't help me complete the homeworks at all. I always had to look things up in other places to get the right answers. Need more problem solving and less describing the math behind everything.

par 昊 黄

•Jan 06, 2018

As an amateur photographer who is interested in post-processing, I came here to find more about how image processing softwares work. Sometimes it took me lots of time to catch up what the professor was teaching. This course is not friendly to the person who does not have basic knowledge about signal processing and math. And the professor's accent is quite noticeable to me, a non-native English speaker, plus there are tons of errors and [UNKNOWN] in the subtitles, which is the one biggest challenges I had met. But frankly speaking, This course is great in the most of aspects, I have learnt a lot from it. The most of tests are relative easy compared to the lectures.

BTW, In the final MATLAB test, there is a hint about normc function, that is useless for the student who is using MATLAB online because the function belongs to additional toolkits that online users will not have.

par 刘学柱

•Sep 19, 2016

感觉是印式英语，太难懂，承受不了了。

par Nikolay K

•Nov 06, 2017

The lecturer tries to fit too much information into the limited size of the lectures, so he has to skip too much, so many formulas are given with not enough explanation. I think the only folks who can follow are the people who already know all the math from other sources.

par Petr V

•Aug 15, 2017

I had to quit the course after the first week. Prof. Katsaggelos gave examples including MRI where he states that "Each pulse causes a corresponding pulse of radio waves to be emitted by the patient's tissues." That of course is nonsense. Tissues does not emit any radio waves. The coils register variation in magnetic field through induction of current. How I am supposed to trust someone whom I catch presenting false information about something I know very well (I am a radiologist). How can I be sure that the information I know nothing about and want to learn is actually relevant and true? It is a question of credibility. He doesn't have to dig in what he doesn't understand. Also, and I am sorry to say that, the presentations are not really engaging which might of course be my personal taste.

par Soh W K

•Jan 17, 2019

By far one of the most challenging courses presented in Coursera. This course should be classified as an Advanced course for people with Engineering Mathematics Background, else it would be tremendously difficult to follow. I truly enjoyed the course presented here, and once the fundamentals are understood, it would be quite easy to understand all the Imaging Processing Technique presented. Now I am confident of using Matlab to try out the Algorithms to do Image and Video Processing!

par Jenkins

•Mar 15, 2019

Was very useful to brush up the image and video processing concepts.

par Sufian K

•Jan 19, 2020

The course need more practical examples and more explanation for how to apply the theory using computer software. But over all the course explain the theory in details without making it so complicated. It was a great experience.

par Liqing S

•Jul 12, 2020

This is just fundamentals of image processing. The course has breadth but lack of depth. There are lots of materials but the course only dips the water. I would rather have a course dedicated to some certain algorithm with more details and depth than just quickly survey the topics.

par Chen L

•Jun 22, 2020

A comprehensive introduction to the theoretical aspect of the subject, with many well designed hands-on practice. The course is not very friendly to complete newcomers who don't have any existing experience, but serves as a great starting point

par Naveen V

•Sep 14, 2019

This course covers a wide range of topics starting from Signals and Systems all the way to applications of Machine Learning in the domain of Image Processing. One must not be fooled by the short length of the Video Lectures , as every second is packed with information. A minor lapse in concentration may force you to replay the Video Lectures. Upon completion of this course, one would gain a good understanding of topics in Video Compression and Image Processing and will be better oriented to learn and take on challenges. Brushing up one's knowledge on Digital Signal Processing and Differential Calculus would be highly beneficial in following the contents of the mathematical and signal processing portions of the lecture.

par Zsolt V

•Jul 24, 2016

A good course, with a tremendous amount of information. I would suggest to split it up to (at least) two courses. Prof. Katsaggelos is very enthusiastic, the summaries in the beginning and in the end are useful. Maybe, it would be helpful for the students to summarize the necessary mathematical knowledge for this course, because this topic is really colorful in mathematical point of view. As a mathematician, I really enjoyed that, but an outsider may not feel the same. All in all, if somebody learns all of the topics, he/she will have a very strong basis in this topic.

par Tibor E

•Feb 05, 2017

It is a well structured course covering a lot of ground that is certainly worthy of your time. The only aspect that I found could do with some improvement was the practical side: the programming exercises could have been a bit more challenging or rather they may have demonstrated the more advanced or state-of-the art techniques rather than focusing only on the basics. I recommend this course to everyone working with images and video.

par Nazia N N

•Apr 28, 2018

It was a great intuitive journey of digital image processing. The course seemed a little difficult but replaying the videos, making notes and discussing the problems in forums really helped to clarify the doubts. The problems are tricky, it really helps to underpin the concepts. Hands on experience with MATLAB really took the experience to the next level! Thanks coursera and Prof. Aggelos .K. Katsaggelos.

par Aldo A

•Mar 23, 2020

A really great class that is not afraid to show the math and theory behind many image and video processing tasks. Definitely felt like the class would have similar material at NU.

I would say my main complaint is that I wish there were at least 5-10 times the number of programming assignments (even if optional) per week. Honestly, the final problem of the final week was fun even if simple.

par M'Hand K

•Mar 05, 2017

Great course on image and video processing. I learned many interesting techniques that will be very useful in my academic research. The instructor is very knowledgeable, and I'm looking forward to starting other courses with coursera. I highly recommend this course for anyone who wants to understands from the basics to the most modern methods in image and video processing.

par Taizo N

•Nov 30, 2016

I work for a software company, and develop image processing software. I think this course covers pretty much a wide range of digital image and video processing field. Assignment are moderate, well solved with lectures and materials only. You would have a comprehensive skills and knowledge you need to get into this field after finishing this course.

par u.mahendra n

•Mar 27, 2017

i like the way of teaching .This subject is very useful to for me .Its related to broad casting side .And how to maintain keying in electronic media to visualize the picture clarity .I appreciate that are using chrome keying . I thankful to you sir .This subject helpful for my further studies . Thank you .

par Mohaned K S E

•Jul 07, 2016

The only disadvantage which i've noticed in this course, is that the examples shown in the lesson are not correct number-wised,which make a little-bit confusion to the students.

for example,the critical and oversampling slides, the shown sampled picture is totally independent to the frequency domain shown beside.

par Federico D

•Nov 14, 2017

Extremey intersting course that allows to understand the principles of digital image and vido analysis by "getting our hands dirty" with a commercial code. Starting from scratch I am getting used to the main applications of the explained alogorithms that are proving to be very successful for my research topic .

par Shobhit B

•Jun 08, 2016

This is one of the best introductory courses on image processing. The lectures are very good and cover a large variety of topics.

The only thing that I didn't like about this course is that the homework problems do not cover all the content. The programming problems should be designed to be more challenging.

par Leandro R M

•Jan 04, 2017

It's a great course although it'll probably make you go back to math very often but in the end you'll feel so happy because all the parts starts to make sense, I mean, you can understand mostly of what happens behind the scene (in digital video/image processing) and you read books to deepen your knowledge.

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