Catolog information:Image transforms, filter design, spectrum estimation, enhancement, restoration, data compression and reconstruction from projectionsPrerequisites: ECE 340, 503, 529Instructor: Robert SchowengerdtECE402,621-2706, [email protected] hours for this course: MTWTh 1-2Course website: http://www.ece.arizona.edu/~dial/ece533/ece533.htmlTextbook:none required; extensive notes will be provided (posted on the class website). References:Digital Image Processing, 2nd Ed, R. C. Gonzalez and R. E. Woods, Addison-Wesley, 2002Image Processing - The Fundamentals, Maria Petrou and Panagiota Bosdogianni, Wiley, 1999Digital Image Processing, Castleman, K., Prentice-Hall, 1996Two-Dimensional Signal and Image Processing, Lim, Jae S., Prentice-Hall, 1990 Fundamentals of Digital Image Processing, Anil K. Jain, Prentice-Hall, 1989Digital Picture Processing, A. Rosenfeld and A. C. Kak, Academic Press, 1982Digital Image Processing, W. K. Pratt, Wiley, 1978Absences and late assignments, regradingZero credit will be given for late homeworks or missed exams, unless it has been pre-arranged with my approval. Homeworks and exams will not be regraded unless a grading mistake is found.Homeworks, exams and gradingThere will be about 10 homework assignments (mix of math and computing problems, graded by course grader), two mid-term exams and an optional final exam (all graded by instructor). The relative weights on your final semester score will be:homeworks: 50%exams: 30% highest score, 20% lowest scoreI will have your semester grades by the last day of class. There will be an optional, comprehensive final exam for students who would like an opportunity to improve their grade. If you take the final and your score is higher than your lowest score on the previous two exams, I’ll replace that score with the final score and recalculate your semester average and grade. If your score on the final is lower than either of the two previous exams, the original semester grade will remain as your grade.SoftwareComputing assignments will require either MatLab or tclSADIE (see website).ECE/OPTI 533 Digital Image Processing Spring Semester, 2003Course Syllabus 1Schedule (this target schedule may change)class date content1 Jan16 introduction and overview2 Jan21 1-D math review, image representations3 Jan23 2-D math functions4 Jan28 2-D math operations5 Jan30 optical image formation6 Feb4 image scanning7 Feb6 image enhancement I (radiometric)8 Feb11 image enhancement II (convolution)9 Feb13 2-D Discrete Fourier Transform10 Feb18 image enhancement III (Fourier)11 Feb20 2-D filter design12 Feb25 image noise I13 Feb27 image noise II14 Mar4 image noise III15 Mar6 mid-term exam #116 Mar11 image coding I17 Mar13 image coding II18 Mar18 Spring Break19 Mar20 Spring Break20 Mar25 image warping I21 Mar27 image warping II22 Apr1 human vision system23 Apr3 multispectral image processing I24 Apr8 multispectral image processing II25 Apr10 image restoration I26 Apr15 image restoration II27 Apr17 3-D imaging and reconstruction I28 Apr22 TBD (travel)29 Apr24 TBD (travel)30 Apr29 3-D imaging and reconstruction II31 May1 mid-term exam #232 May6 last class33 May11 final exam (optional)ECE/OPTI 533 Digital Image Processing Spring Semester, 2003Course Syllabus