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picture1_Processing Pdf 179143 | E9241 Item Download 2023-01-29 22-10-04


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File: Processing Pdf 179143 | E9241 Item Download 2023-01-29 22-10-04
e9 241 august 2 1 digital image processing instructor chandra sekhar seelamantula email chandrasekhar iisc ac in teaching assistant deepak g skariah email deepaks iisc ac in department electrical engineering ...

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                                      E9 241 August 2:1
                                  Digital Image Processing
                                           Instructor
                                     Chandra Sekhar Seelamantula
                                    Email: chandrasekhar@iisc.ac.in
                                       Teaching Assistant
                                         Deepak G Skariah
                                      Email: deepaks@iisc.ac.in
                                  Department: Electrical Engineering
                                       Course Time: 5-6.30 PM
                                        Lecture venue: B 306
Detailed Course Page: https://sites.google.com/site/chandrasekharseelamantula/teaching/e9-241-2-1-digital-image-processing
      Announcements
      The announcements are related to assignments, class tests, demos, lab sessions, etc. The announcements are
      made on Piazza.
      Brief description of the course
      The course is ideal for those who have a background in Digital Signal Processing or Harmonic Analysis. The
      course covers various aspects of two-dimensional signal processing, the theory, and various applications.
      Prerequisites
      Digital Signal Processing or Harmonic Analysis
      Syllabus
      Continuous image characterization, sampling and quantization, 2D Fourier transform and properties,
      continuous/discrete image processing, rotation, interpolation, image filtering (shift-invariant filters, bilateral
      filters, nonlocal means), spatial operators, morphological operators, edge detection, texture, 2-D transforms
      (discrete Fourier transform, discrete cosine transform, Karhunen-Loève transform, wavelet transform), image
      pyramid, image denoising, segmentation, restoration.
      Course outcomes
      The students would get a firm foundation in 2-D signal processing and be able to handle real-world image
                                             Page 1/2
     processing problems and develop image processing software.
     Grading policy
     Class tests: 30%
     Assignments (written and programming): 20%
     Finals (theory): 30%
     Finals (programming): 20%
     Assignments
     The assignments include both problem solving and programming components. On the average, there is one
     assignment every 10 days with a submission time of 10 days.
     Resources
     Lim J. S., Two-dimensional signal and image processing, Prentice Hall, 1990.
     Jain A. K., Fundamentals of digital image processing, Prentice Hall, 1989.
     Gonzalez  R. C. and Woods R. E., Digital image processing, Prentice Hall, 2008.
     Dudgeon D.E. and Merserau R. M., Multidimensional digital signal processing, Prentice Hall Signal
     Processing Series, 1983.
     Augmented by custom-made videos and YouTube videos.
                                         Page 2/2
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...E august digital image processing instructor chandra sekhar seelamantula email chandrasekhar iisc ac in teaching assistant deepak g skariah deepaks department electrical engineering course time pm lecture venue b detailed page https sites google com site chandrasekharseelamantula announcements the are related to assignments class tests demos lab sessions etc made on piazza brief description of is ideal for those who have a background signal or harmonic analysis covers various aspects two dimensional theory and applications prerequisites syllabus continuous characterization sampling quantization d fourier transform properties discrete rotation interpolation filtering shift invariant filters bilateral nonlocal means spatial operators morphological edge detection texture transforms cosine karhunen loa ve wavelet pyramid denoising segmentation restoration outcomes students would get firm foundation be able handle real world problems develop software grading policy written programming final...

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