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VIZA 654 / CPSC 646 - The Digital Image
Fall 2007

Instructor: Dr. Wei Yan

Email: wyan@archmail.tamu.edu
Telephone: (979) 845 0584
Office Hours: Mondays and Wednesdays 3:30PM - 5:00PM, Langford A318

TA: Patrick O'Brien


Email: ob1@viz.tamu.edu
Telephone: (832) 651 5812
Office Hours: Mondays 1:00PM - 3:00PM and Wednesdays 1:00PM - 3:00PM, Visualization Lab
                    You can also meet with me by appointment.

Course Website: http://www-viz.tamu.edu/courses/viza654/07fall/

Course Directory: /usr/local/misc/courses/viza654/2007

Introduction

Tools and techniques for the generation, handling and analysis of two-dimensional digital images. Image representation and storage, display, media conversion, painting and drawing, warping, color space operations, enhancement, filtering, and manipulation.

Just as digital sound has become the standard for high-quality audio recording, the digital image is becoming the standard form of electronic image. Digital images have the advantages of lossless storage, transmission, and retrieval. Their form greatly facilitates generation, manipulation, and display within a computing environment, and they provide a natural syntax for image representation that pervades the world of computer graphics and visualization. Thus, an understanding of the nature, form, and technology of the digital image is essential to a visualization practitioner.

Text and Handout Materials

  • Donald House, The Digital Image, Course Notes
  • Materials Found in Course Home directory - /usr/local/misc/courses/viza654/2007/

Course Objectives

This course will provide a thorough grounding in the state of the art in the treatment of digital images, particularly within the context of computer graphics, and digital effects. It is designed to prepare students to
  • understand existing systems for storage, display, transformation and manipulation of digital images
  • write their own software for working with digital images
  • undertake creative work and research involving digital images
Students read, discuss, and are tested on hand-out material, and complete a series of exercises on the computer. Many of the exercises will involve programming and making use of graphics libraries. Work may be done on any computer supporting C++, OpenGL and the OpenGL interface API GLUT (OpenGL Utility Toolkit), and will involve a brief study of professional image manipulation software.

Course Outline

  1. The Fundamental Nature of Digital Images
    • sampling
    • point spread
    • reconstruction
  2. Digital Representation and Display of Images
    • bitmaps and pixmaps
    • framebuffer hardware
    • CRT displays
    • color and color spaces
    • color lookup tables
    • gamma correction
    • color manipulation techniques
  3. Archival Storage of Images
    • image file formats
    • conversion between formats
    • compression schemes
  4. Compositing
    • alpha channel and opacity
    • image combination operations
    • bluescreening
  5. Filtering Algorithms
    • convolution filters
    • morphological operators
  6. Image Warping
    • general image maps
    • forward warp
    • inverse warp
    • affine warps
    • projective warps
    • bilinear warp
  7. Sampling, Filtering and Reconstruction
    • sampling and the aliasing problem
    • spatial convolution filtering techniques
    • resampling and the reconstruction problem
    • reconstruction techniques
  8. General Warping and Morphing Algorithms
    • scanline warp algorithm
    • morphing as warp + compositing
    • feature based morphing algorithms
  9. Frequency Domain Representation of Images
    • the sampling theorem
    • ideal vs. practical filtering
    • repair of images
  10. Advanced Topics (time permitting)
    • lossy image compression (JPEG and wavelet)
    • NPR image methods

Performance Evaluation

Grading will be based on perfomance on a set of 8 homework assignments, 9 quizzes, a final project, and class participation using the following percentage distribution:
  • Homeworks: 60%
  • Quizzes: 10%
  • Final Project: 20%
  • Class Participation: 10%

Regular homework programming projects will involve writing and modifying image handling software on the SGI workstations. Code may be written in C or C++ and use the OpenGL and GLUT libraries. Other nonprogramming homework projects will involve experimenting with software. Students will also complete a final term programming project of their own design. Homework problems and the final project will be graded on a 100 point scale. The final grade will be given by a letter based on weighted average points. Points and letters will be given by the following evaluation:

Letter grade Point grade (max 100) Quality of work
A points>=90 Meets all requirements and is especially distinguished. Extraordinarily distinguished work (awarded only rarely) for 100.
B 90>points>=80 Completely satisfactory, meets all requirements
C 80>points>=70 Generally satisfactory but has errors or does not meet all requirements
D 70>points>=60 Unsatisfactory
F points<60 Failure

Work will be considered on time if it is submitted by 12:00 midnight of the due date. Except for unusual circumstances agreed to in advance by the instructor, late homework will incur a penalty of 5% of that homework points per day. The class participation grade is the instructor's subjective judgement of student performance. He will take into account such things as attendance and preparation for class as evidenced by informed classroom discussion.

Reference Reading Material

  • Brinkmann, The Art and Science of Digital Compositing, Morgan Kaufmann, 1999
  • Foley, Van Dam, Feiner and Hughes, Computer Graphics Principles and Practice, Addison Wesley, 1990.
  • Gomes and Velho, Image Processing for Computer Graphics, Springer-Verlag, 1997.
  • Gonzalez and Woods, Digital Image Processing, Addison Wesley, 1992
  • Sayood, Introduction to Data Compression, Morgan Kaufmann, 1996
  • Wolberg, Digital Image Warping, IEEE Computer Society Press, 1990
  • Shreiner, Woo, Neider and Davis, OpenGL Programming Guide, The Official Guide to Learning Opengl, Version 1.4, 4/E, Addison Wesley

Plagiarism

The handouts used in this course are copyrighted. By "handouts," I mean all materials generated for this class, which include but are not limited to the course notes, syllabi, exams, problems, in-class materials, review sheets, additional problem sets, and the contents of the class World Wide Web site. Because these materials are copyrighted, you do not have the right to copy the handouts, unless I expressly grant permission. For the contents of class World Wide Web sites, you have permission to make printouts strictly for your use in this class.

In this course, we want to encourage collaboration and the free interchange of ideas among students and in particular the discussion of homework assignments, approaches to solving them, etc. However, we do not allow plagiarism, which, as commonly defined, consists of passing off as one's own the ideas, words, writings, etc., which belong to another. In accordance with this definition, you are committing plagiarism if you copy the work of another person and turn it in as your own, even if you should have the permission of that person. Plagiarism is one of the worst academic sins, for the plagiarist destroys the trust among colleagues without which research cannot be safely communicated.

If you have any questions regarding plagiarism, please consult the latest issue of the Texas A&M University Student Rules, under the section on Academic Misconduct.

Americans with Disabilities Act

The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact the Office of Support Services for Students with Disabilities in Room 126 of the Student Services Building. The phone number is 845-1637.

Academic Integrity Statements

AGGIE HONOR CODE  “An Aggie does not lie, cheat, or steal or tolerate those who do.”
Upon accepting admission to Texas A&M University, a student immediately assumes a commitment to uphold the Honor Code, to accept responsibility for learning, and to follow the philosophy and rules of the Honor System. Students will be required to state their commitment on examinations, research papers, and other academic work. Ignorance of the rules does not exclude any member of the TAMU community from the requirements or the processes of the Honor System.For additional information please visit: www.tamu.edu/aggiehonor/

Acknowledgements

Thanks to Prof. Donald House, who developed this course during the past years and provided all course materials and strong support to the instructor.