CIS Special Topics Offerings

SPECIAL TOPICS FOR WINTER QUARTER 20092

UNDEGRADUATE COURSES

1051-553-01    Special Topics: Remote Sensing Systems, Instructor: John Kerekes

This course develops knowledge and understanding of the design and analysis of optical remote sensing systems for Earth remote sensing. Building on general imaging fundamentals learned earlier in their program, students will learn domain specific tools and techniques for analyzing airborne and satellite sensor systems for the optical spectral imaging of Earth. Through a combination of classroom and laboratory experiences, students will learn about the propagation of photons and signals from the Sun through the formation of a digital image. The course will emphasize a linear systems modeling perspective and provide the students the background to understand, model, and predict remote sensing imaging system performance. (1051-370, 1051-452, 1051-453, or permission of instructor)  Class 4, Credit 4 (F or W)

Text: John R. Schott, Remote Sensing: The Image Chain Approach, 2^nd Edition Academic Press

1051-553-70/2076-454-70      Holography, Instructor: Terry Kessler T/R 6:00 to 7:50 PM

Introduction to holographic and diffractive imaging. Lectures and demonstrations cover the materials, processes and applications of the fundamental types of holograms. Laboratory investigations provide hands-on experience with the construction and playback or transmission, reflection and white-light holograms. (Algebra and physics) Credit  4 (Lab on either T or R immediately following lecture)

2065-552-70       Digital Color Management, Instructor: Ed Giorgianni T/R 6:00 to 7:50 PM

This course offers a comprehensive study of the methods and techniques used to manage and interchange color in modern digital color-imaging systems. The principles of colorimetry and densitometry will be reviewed and applied specifically to color imaging applications. The fundamental colorimetric properties of color imaging media, devices and systems will be explored and compared. Digital color encoding principles will be examined, and the features and limitations of various digital color encoding methods will be described. The three basic paradigms underlying all color managed systems will be discussed, and a new unified paradigm that encompasses all three basic paradigms will be introduced. The color encoding requirements and associated colorimetric transformations required to support that paradigm will be discussed. Various simple and complex systems based on the unified paradigm, including a Digital Cinema system currently being developed by AMPAS and SMPTE, will be described.  Prerequisite: 1051-402 (Color Science) Class 4, Credit 4 (W)

GRADUATE COURSES

1050-753-01    Appearance of Materials, Instructor: James Ferwerda

The visual properties of materials provide critical information in a vast range of human domains. For example in a restaurant, material appearances tell us whether the silverware is clean or dirty and whether the sushi is fresh or spoiled. In a hospital, material appearances can tell a doctor about the kind and severity of a patient’s illness. On the used car lot material appearances can tell a buyer if a car has been in an accident. However despite its important role, knowledge about material appearance is far from systematic and is dispersed across many literatures including: physics, biology, chemistry, engineering, psychology and more recently computer graphics and computer vision. I this seminar course we will read and discuss key papers on the topic of material appearance and will work toward building an interdisciplinary view of this important subject. Credit 1

1051-753-01       Computational Methods for Imaging Science, Instructor: Harvey Rhody

Computational science is a recognized general discipline for constructing mathematical models and numerical techniques to simulate and analyze scientific, engineering and social problems. Computational methods for imaging science uses the same techniques but focuses on problems that arise in the field of imaging science. The purpose is to gain insight and understanding to enable the development of imaging systems to solve problems in a broad range of applications that use imaging as a fundamental sensing and visualization component. Graduate standing. Class 4, Credit 4

1051-753-02             Introduction to Multi-view Imaging, Instructor: Harvey Rhody

Multi-view imaging has roots in computer vision, photogrammetry and sensor fusion and is important for applications such as scene modeling, scene understanding, robot navigation, and use of information from any collection of sensors that include geometric information in their products. Application domains include remote sensing, medical imaging, visually assisted navigation, and virtual scene reconstruction. Computational techniques are constructed with a mathematical framework that is based upon the perspective geometry of multiple views. This course covers this mathematical background and related computational techniques. Each topic is accompanied by exercises to enlighten and develop both the theory and implementation of algorithms for basic techniques such as image registration, camera calibration, recovery of scene geometry, image fusion, use of LIDAR data with images and construction of synthesized scene views. Expected background is knowledge of algorithms for processing individual images, programming skills in Matlab or IDL, and knowledge of linear vector space mathematics. Prerequisite: Graduate standing and 1051-782 Digital Image Processing or equivalent, or permission of instructor. Class 4, Credit 4

Text: Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision, 2^nd Ed., Cambridge, 2003