In the past, image acquisition techniques and image processing were considered to be mostly independent of each other. However, people working in the field are aware that many problems can only be solved by carefully balancing both to solve the actual task at hand. So far, there are only empirical formulas and little in the way of solid fundamentals.
Recent developments in computational imaging also provide the basis to look at image acquisition and image processing concertedly. The basic concept was initially developed for and applied to computer graphics ("image-based rendering") before moving into consumer applications. In the area of machine vision, computational imaging makes it possible to develop visual inspection systems.
Examples include acquisition techniques using a widened depth of focus or systems allowing capture and analysis of complex optical surface characteristics as well as 3-D structures at the same time.
This course conveys fundamental knowledge on the basic principles of computational imaging, introduces the key practical methods and illustrates future prospects.