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Avis et commentaires pour l'étudiant pour Fondements de l'image numérique et du traitement des vidéos par Université Northwestern

1,096 notes
226 avis

À propos du cours

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....

Meilleurs avis


Mar 21, 2019



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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1 - 25 sur 220 Examens pour Fondements de l'image numérique et du traitement des vidéos

par 刘学柱

Sep 19, 2016


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 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 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 Jenkins

Mar 15, 2019

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

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 rahul k

Nov 18, 2018


par Surya K

Nov 17, 2018

useful course

par Ankit K

Nov 07, 2018

This course was really helpful in understanding the difficult concepts of image and video processing. I highly encourage all the college students to take this course if they atre willing to improve their grades or are just interested in learning something new.

par 15MIS0361 S V

Nov 10, 2018

This course was very helpful to me and I think this would be helpful to my carreer.

par wuqimin

Nov 28, 2018

A course not easy for

par Abhishek J

Nov 13, 2018

very good

par Aditya R

Nov 12, 2018

Really brief and descriptive

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 Liubov F

Jan 18, 2019

Спасибо за этот курс. Он очень интересный и заставляет много думать. А это очень хорошо. Главное, что эти знания очень нужны в современной жизни.

par Vítor R

Mar 04, 2019

Professor Aggelos Katsaggelos and his team have greatly succeeded in manufacturing such magnificent material. It has been a very rewarding and motivating experience to learn directly from one of the best. I'm much grateful to everyone involved that devoted time into the making of this course.


Mar 09, 2019

very good and easy to understand about Images and its process

par Keerthi v

Mar 13, 2019

marvellous teaching !!

par Kashish M

Mar 15, 2019

awesome !!! had fun learning this.

par Naitik s

Mar 20, 2019

great one

par Sayantan R

Mar 20, 2019

Great course! Relevant to the current progress in tech fields!

par Foudil A

Jan 14, 2019

Excellent. I would like to thank all the team of coursera and professor

Aggelos K. Katsaggelos for his pedagogical way of presenting the course.

par Raghavendra S

Nov 30, 2018

amazing experience thank you for all the important techniques that have been imparted to me won't ever forget it.