Signal Processing and Imaging Systems
This course introduces the basic concepts of estimation and detection. For a better understanding, each of these concepts is illustrated on real problems related to optical imaging or image processing. This allows in particular to make more concrete the central notions of noise and optimality of treatments. The aim is that at the end of this course, a student will be able to formulate a problem of information extraction in a noisy signal or image in rigorous terms, to solve this problem in an optimal way, and to evaluate the performance of this solution.
Bibliographie
- Ph. Réfrégier, Noise Theory and Application to Physics: From Fluctuations to Information (Springer, New-York, 2004).
- S. M. Kay, Fundamentals of statistical signal processing - Volume I : Estimation Theory (Prentice-Hall, Englewood Cliffs, 1993).
- S. M. Kay, Fundamentals of statistical signal processing - Volume II : Detection Theory (Prentice-Hall, Englewood Cliffs, 1993).
- F. Goudail, Ph. Réfrégier, Statistical image processing techniques for noisy images: an application oriented approach, (Kluwer Academic, New York, 2004).