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Broad topics in image and video processing are covered and it was very useful to grasp what kind of techniques are being used in this field. Although most of the subjects were presented in a very comprehensive manner, some contents (maybe advanced ones) still have rooms for improvement.

For the home work assignments, most of the programming problems were too easy (the one in week 12 was challenging, so other weeks could have had problems with equal difficulty.) Also, some problems' statement seemed somewhat ambiguous. If read carefully, the meaning is clear, but since people from all over the globe are taking the course, it might be helpful if they were written in more clear way.

Lastly, maybe because the course was uploaded several years ago, the activity of the forum was very low, which spoiled one of the benefit of using MOOC.

The course content is great. The professor has delivered the material in a simple and straight forward way. There are many results which we can utilize straight away and experiment with. The only drawback was that the quizzes were theoretical,with just one problem dedicated to programming. To get more benefits out of this course certainly we have to do some extra reading Nevertheless it was a great introductory course. Will surely recommend it to others.

I think week 3 is the most important topic in image/video signal processing and the maths is really important here. I would say that despite image recovery is taught in 2 weeks, the focus is bit lost and touched too many topics without going deeper for a specific one.

I probably would suggest to have Laplacian pyramid and similar stuff just after frequency analysis, it will help student to understand better in later applications.

Best suited for the beginners. Anyone who has no experience with signal processing except the mathematical representation of any signal can enjoy this course. The programming problems are easy for those who have basic knowledge of the software (MATLAB). Last two modules (Segmentation (week 11), Sparsity (week 12)) are the most exciting ones (for me). Finally, the course lacks the resources for further studies.

Very good overview of theory, specific algorithms, and some practice of application in MATLAB. There's a lot of material to cover and the videos are longer, requiring self-pacing throughout the individual lectures. Some of the weeks are very challenging. Extracurricular study, practice and implementation helped in areas where I had yet to encounter supporting material and/or prerequisites.

This course has all basic methods on image processing but has a few examples to demonstrate each of them. So it's rather difficult to understand all the materials.It's necessary to research further on each method. In other words it's better to pass some graduated courses like information theory or digital communication to understand it better.

Well worth the time. Topics are clearly explained most of the time. I was getting a bit lost in the math towards the very end (last couple of weeks), but even though details were hazy, I think the general concept was conveyed well. The labs could be a bit more insightful for a few of the weeks but were overall good.