EE 610 - Image Processing

Course content
  • Image representation, basics of colorimetry, KL transforms, two dimensional transforms, image enhancement, edge detection, histograms. 
  • Image restoration : sources and models of image degradation, point spread functions (psf), stochastic psf, noise in images. 
  • Formulation of image restoration problem least square, minimum mean square error (MMSE) and homomorphic filter restoration, linear and non-linear restoration techniques.
  • Mathematical morphology, computer tomography.
References
  • W.K. Pratt: `Digital image processing", Prentice Hall, 1978.
  • A. Rosenfold and A.C. Kak: `Digital image processing", Academic Press, 1976.
  • A. Rosenfold and A.C. Kak: `Digital image processing", Vols 1 and 2, Prentice Hall, 1986.
  • H.C. Andrew and B.R. Hunt, Digital image restoration, Prentice Hall, 1977.
  • K.R. Castleman: `Digital image processing", Prentice Hall, 1979.
  • A.K. Jain: `Fundamentals of digital image processing", Prentice Hall, 1989
Pre-requisite : N/A
Total credits : 6 credits - Lecture
Type : Core Course
Duration : Autumn 2022
Name(s) of other Academic units to whom the course may be relevant : N/A