A Visualization Toolkit for Teaching, Learning and Experimentation in Image Processing

Due to their intrinsic and abstract difficulties, image processing (IP) courses are in general of graduate and postgraduate level. For efficient IP teaching, a special focus needs be set on students' experimental works. The scope is to allow students to concretize and try out the studied technology. Visualization tools for IP's basic aspects are also needed by teachers that desire achieving better pedagogical results. Indeed, the visualization of the impact that an algorithm has on the visual data (such as e.g. filtering algorithm) is cognitively superior to the plain textual description. Students should then be able to actively and quickly complement their lectures by processing and manipulating images and even constructing personal IP tools. It is this hand-on experimentation that can significantly facilitate the learning of the mathematical concepts of image processing. The toolkit presented in this article responds to the above requisites