Imaging Science Ph.D.

Imaging Science, Ph.D. degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
IMGS-606
Graduate Seminar I
This course is focused on familiarizing students with research activities in the Carlson Center, research practices in the university, research environment and policies and procedures impacting graduate students. The course is coupled with the research seminar sponsored by the Center for Imaging Science (usually weekly presentations). Students are expected to attend and participate in the seminar as part of the course. The course also addresses issues and practices associated with technical presentation and technical writing. Credits earned in this course apply to research requirements.
1
IMGS-607
Graduate Seminar II
This course is a continuation of the topics addressed in the preceding course Imaging Science Graduate Seminar I. The course is coupled with the research seminar sponsored by the Center for Imaging Science (usually weekly presentations). Students are expected to attend and participate in the seminar as part of the course. The course addresses issues and practices associated with technical presentations. Credits earned in this course apply to research requirements.
1
IMGS-609
Graduate Laboratory I
This laboratory course is intended to familiarize graduate students with many concepts, tools, and techniques necessary for completion of the Imaging Science graduate curriculum. Students will work in a variety of areas including scientific programming, numerical analysis, imaging system analysis, and characterization. (Pre-requisite: Graduate standing in Imaging Science or permission of the instructor.)
2
IMGS-613
Probability, Noise, and Systems Modeling
This course develops models of noise and random processes within the context of imaging systems. The focus will be on stationary random processes in both one dimension (time) and two dimensions (spatial). Power spectrum estimation will be developed and applied to signal characterization in the frequency domain. The effect of linear filtering will be modeled and applied to signal detection and maximization of SNR. The matched filter and the Wiener filter will be developed. Signal detection and amplification will be modeled, using noise figure and SNR as measures of system quality. At completion of the course, the student should have the ability to model signals and noise within imaging systems.
3
IMGS-616
Fourier Methods for Imaging
This course develops the mathematical methods required to describe continuous and discrete linear systems, with special emphasis on tasks required in the analysis or synthesis of imaging systems. The classification of systems as linear/nonlinear and shift variant/invariant, development and use of the convolution integral, Fourier methods as applied to the analysis of linear systems. The physical meaning and interpretation of transform methods are emphasized.
3
IMGS-619
Radiometry
This course is focused on the fundamentals of radiation propagation as it relates to making quantitative measurements with imaging systems. The course includes an introduction to common radiometric terms and derivation of governing equations with an emphasis on radiation propagation in both non-intervening and turbid media. The course also includes an introduction to detector figures of merit and noise concepts.
3
IMGS-620
The Human Visual System
This course describes the underlying structure of the human visual system, the performance of those structures and the system as a whole, and introduces psychophysical techniques used to measure them. The visual system's optical and neural systems responsible for collecting and detecting spatial, temporal, and spectral signals from the environment are described. The sources and extent of limitations in the subsystems are described and discussed in terms of the enabling limitations that allow practical imaging systems.
3
IMGS-633
Optics for Imaging
This course provides the requisite knowledge in optics needed by a student in the graduate program in Imaging Science. The topics covered include the ray and wave models of light, diffraction, imaging system resolution.
3
IMGS-682
Image Processing and Computer Vision
This course will cover a wide range of current topics in modern still digital image processing. Topics will include grey scale and color image formation, color space representation of images, image geometry, image registration and resampling, image contrast manipulations, image fusion and data combining, point spatial and neighborhood operations, image watermarking and steganography, image compression, spectral data compression, image segmentation and classification, and basic morphological operators. Projects will involve advanced computational implementations of selected topics from the current literature in a high level language such as Matlab or IDL and will be summarized by the students in written technical papers.
3
 
Specialty Track Course
3
Second Year
IMGS-890
Research & Thesis
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
1
 
Specialty Track Course
3
 
Electives
9
Third Year
IMGS-890
Research & Thesis
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
10
Fourth Year
IMGS-890
Research & Thesis
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
10
Fifth Year
IMGS-890
Research & Thesis
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
2
Total Semester Credit Hours
60