CE 261: Digital Image Processing

handouts location: http://www.cse.ucsc.edu/classes/cmpe261
SSI #110
Tuesday, Thursday 6:00-7:45 PM
Office hours: Tuesday, Thursday 5:00-6:00 PM

Prerequisites: Graduate standing or permission of instructor.

Text: Digital Image Processing by K. Castleman, Prentice Hall, 1996.

Requirements: 7 homeworks (10%) and 4 laboratory assignments (30%), 1 exam (30%), comprehensive final (30%).

The course is to have one exam to be in class and a final. Homeworks and programming projects will be assigned.

Week [1] of April 7:  Intro to image processing, (Ch. 1 & Ch. 2 & Ch. 3)
  
Week [2] of April 14: Image processing applications, Image Vision Libraries, Adobe 
Photoshop, Biological Basis for vision, Color theory (Ch. 4, Ch. 21) HW #1 Lab #1
  
Week [3] of April 21:    Histogram/Point processing (Ch. 5 & Ch. 6 & Ch. 7), HW #2

Week [4] of April 28:    Geometric transforms and image warping, permutation warping 
(Ch. 8 and handouts) HW #3 Lab #2

Week [5] of May 5:    Image based rendering, Light Field/Lumigraph, View morphing, 
three dimensional image processing ((Ch. 8 review )Ch. 22 part, handouts) Test 1. 
  
Week [6] of May 12:    Image based rendering continued, multibase plane stereo/epipolar 
geometry, reconstruction of camera intrinsic and extrinsic parameters, voxel coloring. 
(Ch 15 part, handouts) HW #4

Week [7] of May 19:   Introduction to linear systems theory and The Fourier transform 
(Ch. 9 & Ch. 10) HW #5

  
Week [8] of May 28:   Sampling theory and discrete transforms (Ch. 12 and Ch. 13) 
HW #6 Lab #3 May 26 Exchange day, No class on Tuesday !)

  
Week [9] of June 2:    Low level image processing: Image restoration (Ch. 16) HW #7
  
Week [10] of June 9:   Mid level image processing: Segmentation (Ch. 18) Lab #4

 
 NOTE FINAL TIME CHANGE  

Final
Exam, Tuesday June 16, 7:30 - 10:30 pm .  Soc. Sci I. Room 110 (same as 
regular classroom).

Reference material:

Optional Text: Digital Image Processing by R.C. Gonzales and R. E. Woods, 1992.

Encyclopedia of Graphics File Formats by Murray and vanRyper, 1994

Multidimensional Digital Signal Processing, by Dudgeon and Mersereau, 1984.

Fundamentals of Digital Image Processing, by Anil K. Jain, 1989.

ImageVision Library (TM) Programming Guide, by Neider and Bassler, Silicon Graphics, 1993.

Course Description:

261. Digital Image Processing. Spring. Topics in digital image processing and display: image processing, computer vision, visual perception, digital representation, transformations, sampling, enhancement, restoration, parallel input and output hardware/software systems. Emphasis on algorithms and implementation of computer image processing software. Additional material will include applications such as image based rendering, view morphing, volume rendering, and hardware for digital image processing. The course will introduce students to image processing packages though hands on use, development libraries, and programming hardware accelerated Silicon Graphics workstations through C/C++ application programming. Readings and lectures supplemented by homework, lab exercises, and projects.

Policies:

All course work including homework, programs and exams are intended as individual effort and are graded as such. It's okay to discuss general approaches and algorithms with other students, but this should be done without sharing code. Cheating or plagiarism in any form will not be tolerated. Punishment will match severity of offense. You are responsible for protecting your homework solutions and programs from being copied by others. Do not discard printouts in public places. And don't forget to logout.