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1050-701 Vision and PsychophysicsThis course provides an overview of the human visual system and psychophysical techniques used to investigate it with an emphasis on applications to imaging. The first half of the course covers topics including threshold techniques, one- and multi-dimensional scaling techniques, and psychometric functions. The second half of the course includes discussions of the anatomy and physiology of the visual system and aspects of functional vision ranging from form and color perception to motion and depth perception. (Graduate status in Color Science or permission of instructor) Class 4, Credit 4 (F) 1050-702 Applied ColorimetryThis course covers the principles of color science including theory and application. Topics include CIE colorimetry, the use of linear algebra for color transformations, the Munsell color order system, metamerism, color inconstancy, history and theory of color tolerance equations and spaces, and an overview of color management.(Graduate status in Color Science or permission of instructor) Class 4, Credit 4 (W) 1050-703 Color AppearanceThis course is for students who have an understanding of the applications of colorimetry. It presents the transition from the measurement of color patches and differences to the description and measurement of color appearance. This seminar course is based mainly on review and discussion of primary references. Topics include appearance terminology, appearance phenomena, viewing conditions, chromatic adaptation and color appearance modeling. (1050-701, 702) Class 3, Credit 3 (S) 1050-721 Color Measurement Lab IThis course is the first part of a two-course sequence in which students develop the background and skills required for successful laboratory practice for color science research including data management and analysis, technical writing, and basic programming. Topics include the instrumentation and standardization required for high quality optical radiation measurements, analysis techniques for determining the accuracy and precision of those measurements, the optical properties of objects and radiation, optical and electronic design of spectroradiometric and spectrophotometric instrumentation, the use of standard reference materials for calibration, and evaluation of instrumentation and psychophysical experimentation. (Graduate status in Color Science or permission of instructor) Class 1, Lab 3, Credit 3 (F) 1050-722 Color Measurement Lab IIThis course is the second part of a two-quarter sequence in which students develop the background and skills required for successful laboratory practice for color science research including data management and analysis, technical writing, and basic programming. Topics include the precision and accuracy analysis of color measuring instrumentation, color tolerance psychophysics, and building an imaging colorimeter. (1050-721, Corequisite 1050-701) Class 1, Lab 3, Credit 3 (W) 1050-753 Special TopicsAdvanced topics of current interest, varying from quarter to quarter, selected from the field of color science. Specific topics announced in advance. (Not offered every quarter. Consult the color science graduate program coordinator.) Credit variable 1050-799 Independent StudyAn independent project in an area of color science not covered in the available courses. This project can be experimental research, literature review, or other appropriate work. This course requires a formal proposal and a faculty sponsor. Credit variable 1050-801 Color Science SeminarA seminar course in which students will study the literature in particular areas of color science and present that material to the class. Topics will be based on student interest and current issues in the field. Available to color science MS students or by permission of the instructor. May be taken more than once for credit with permission of coordinator. (Graduate status in Color Science or permission of instructor) Class 1, Credit 1 (F, W, S) 1050-840 Color Science MS ProjectAn independent project in an area of color science that serves as the major culminating experience for students in the Graduate Project Option of the color science MS program. This project can be an experiment, critical literature review, demonstration or other appropriate work. This course requires a formal proposal and faculty sponsor; a written technical report and oral presentation of the results. Credit 4 1050-890 Research and ThesisThesis based on experimental evidence obtained by the candidate in an appropriate topic as arranged between the candidate and the coordinator of the program. Credit variable (minimum of 9 credits for MS) 1050-999 Color Science Co-opCooperative work experience for graduate color science students. Credit 0
1051-706 Introduction to Imaging Science 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). The students are expected to attend and participate in the seminar as part of the course. The course will also address issues and practices associated with technical presentation and technical writing. Credits earned in this course apply to research requirements. Class 1, Credit 1 (F)
1051-707 Introduction to Imaging Science IIThis 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. This 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 will also address issues and practices associated with technical presentation and technical writing. Credits earned in this course apply to research requirements. Class 1, Credit 1 (W)
1051-708 Imaging Science SeminarThis 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. Class 1, Credit 1 (S)
1051-713 Probability, Noise and System Modeling
The purpose of this course is to develop an understanding and ability in modeling 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. Also offered online. (1051-716, 718, 719 or permission of instructor). Class 4, Credit 4 (S)
1051-714 Information Theory for Image SystemsThis course develops a basic understanding of the efficient representation of information for storage and transmission. Classical concepts of information theory are developed and applied to image compression, storage and transmission. The intent is to develop a foundation for the efficient handling of image-based information in imaging systems. Also offered online. (1051-713 or consent of instructor)(offered alternate years). Class 4, Credit 4 (F)
1051-716 Fourier Methods in Imaging SystemsThis course develops the mathematical methods required to describe continuous 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 is discussed first, followed by development and use of the convolution integral, and by a discussion of Fourier methods as applied to the analysis of linear systems, including the Fourier series and Fourier transform. Emphasis is placed on the physical meaning and interpretation of these transform methods. Within the context of image analysis, imaging systems as a linear filter, image enhancement and information extraction, and several basic image processing techniques are also introduced. Also offered online. (Graduate standing in a science or engineering program or permission of instructor). Class 4, Credit 4 (F)
1051-718 Digital Imaging MathematicsThis course provides a basic understanding of imaging systems, image transformations and associated mathematics and computational processes needed for upper-level classes in the imaging science graduate program. Topics covered include: camera models; image projections and rectification; image statistics and point processing; linear and nonlinear image filters; image transforms; image mathematics; and computer algorithms. Some laboratory experiments are included. Also offered online. (1051-716). Class 4, Credit 4 (W) 1051-719 RadiometryThis course is focused on the fundamentals of radiation propagation as it relates to making quantitative measurements with imaging systems. It 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; and an introduction to detector figures of merit and noise concepts. Includes some laboratory experiments. Also offered online.(Graduate standing in a science or engineering program, or permission of instructor) Class 4, Credit 4 (F) 1051-720 The Human Visual System
This course describes the underlying structure of the human visual system and the design of visual displays. The optical and neural systems responsible for collecting and detecting spatial, temporal, and spectral signals from the environment are described and discussed in terms of the "enabling limitations" of the human visual system that allow practical visual displays. Softcopy and hardcopy display systems are described in terms of their spatial, spectral, and temporal characteristics. Some laboratory experiments are included. Also offered online. (Graduate standing in a science or engineering program, or permission of instructor) Class 4, Credit 4 (F) 1051-724 Introduction to Microscopy Using Light, Electrons, and Scanning Probes
This is the first course in a three-quarter microscopy sequence. The purpose of this course is to give the student an overview of the various modes of microscopy for the study of materials. The first part of the course will focus on various modes of light microscopy. The bulk of the course will be devoted to electron microscopy, with the final part of the course devoted to scanning tunneling and atomic force microscopy. Demonstrations will be held in the NanoImaging Lab to reinforce the lecture material. (Graduate student standing in science or engineering, or permission of instructor.) Class 4, Credit 4 (W)
1051-725 Fundamentals of Radiation-Matter Interactions
This is the first course in a three-quarter sequence on the interactions between radiation and matter. The purpose of this course is to present an overview of the many interaction mechanisms involving electromagnetic radiation, charged particles, and neutrons with material systems. The course introduces both classical and basic quantum treatments of these interactions. Topics include the dispersion, scattering, absorption, and emission of electromagnetic radiation by atoms and molecules, the scattering of light by small particles, the concept of a cross-section, mechanism of energy loss by charged particles, , the attenuation of different types of radiations, and a brief introduction to how x-rays and neutrons can be used to probe the structure of materials. (Graduate student standing in science or engineering, or permission of instructor.) Class 4, Credit 4 (F, alternate years)
1051-726 Programming for Scientists and Engineers
A course to prepare graduate students in science and engineering to use computers as required by their disciplines. Covers: the organization and programming of computers at various levels of abstraction (e.g. assembly, macros, high-level languages, libraries), advanced programming techniques, the design, implementation, and validation of large computer programs, modern programming practices, introduction to a programming environment and to a variety of programming languages. Programming projects will be required. Also offered online. Class 4, Credit 4 (W)
1051-728 Design and Fabrication of a Solid State Imaging Camera
The purpose of this course is to provide the student with hands-on experience in building a CCD camera. The course provides the basics of CCD operation including an overview, CCD clocking, analog output circuitry, cooling, and evaluation criteria. Class 1.5, Lab 7.5, Credit 4 (W)
1051-733 Optics
This course will provide the requisite introductory knowledge in optics needed by a student in the graduate program in imaging science. The course will cover geometrical optics; wave nature of light, the Fresnel equations, interference and diffraction, and resolution of imaging systems. Some laboratory experiments are included. Also offered online. (1051-716, 719). Class 4, Credit 4 (W)
1051-736 Geometric Optics
This course leads to a thorough understanding of the geometrical properties of optical imaging systems. A method is developed of performing a first-order design of an optical system, applicable to uniform and gaussian beams. The following topics are included: paraxial optics of axisymmetric systems, Gaussian optics (cardinal points, pupils and stops, optical invariant), propagation of energy through lens systems, basic optical instruments and components, gradient index optics, finite raytracing, introduction to aberrations, geometrical optics of gaussian beams. Also offered online. Class 3, Lab 3, Class 4, Credit 4 (F in class, S online)
1051-737 Physical Optics
The wave properties of light and their application to imaging systems and metrology. Polarization, birefringence, interference and interferometers, spatial and temporal coherence, scalar diffraction theory are covered. (1051-717) Class 4, Credit 4 (W) 1051-738 Optical Image Formation
This course presents a unified view of the formation of images and image quality of an optical system from an applications viewpoint, but with a strict mathematical development. Topics covered are: geometrical and diffraction theory of aberrations, image quality criteria and MTF, MTF tolerance theory, image formation with coherent light. Throughout the course, the problem of image formation is treated also in its inverse form of designing an optical imaging system that satisfies a given set of specifications. (1051-737) Class 3, Lab 3, Credit 4 (offered alternate years, offered 2006-07) (S) 1051-739 Principles of Solid State Imaging
This course covers the basics of solid state physics, electrical engineering, linear systems and imaging needed to understand modern focal plane array design and use. The course emphasizes knowledge of the working of infrared arrays. (Optics, Linear Systems) Class 4, Credit 4 (F)
1051-742 Test Focal Plane Array
An introduction to the techniques used for the testing of solid state imaging detectors such as CCDs, CMOS and Infrared Arrays is provided. Focal plane array users in industry, government and university need to ensure that key operating parameters for such devices either fall within an operating range or that the limitation to the performance is understood. This is a hands-on course where the students will measure the performance parameters of a particular camera in detail. While this course can be taken individually, students will obtain maximum educational value by taking it as the third part of a sequence of imaging science courses preceded by 1051-739 Principles of Solid State Imaging Arrays and then 1051-728 Design and Fabrication of a Solid State Camera. (Graduate status in imaging science or permission of instructor). Class 2, Lab 6, Credit 4 (S)
1051-749 Color Reproduction
This course presents the concepts required for an understanding of the relationships between mean-level input and output in various color imaging systems. Analog, digital, and hybrid color imaging systems will be covered. Special emphasis will be given to mean-level reproduction in photography, printing, and television. Offered online. Credit 4 (W)
1051-753 Special Topics in Imaging Science
Advanced topics of current interest, varying from quarter to quarter, selected from the field of imaging science. Specific topics announced in advanced. (Not offered every quarter. Consult the imaging science graduate program coordinator.) Credit variable
1051-761 Sensors and Radiometric Image Analysis
This course introduces the students to the governing equations for radiance reaching an aerial or satellite based imaging systems. It then covers the properties of these imaging systems with an emphasis on their use as quantitative scientific instruments. This is followed by a treatment of methods to invert the remotely sensed image data to measurements of the Earth’s surface (e.g. reflectance and temperature) through various means of inverting the governing radiometric equation. A number of approaches for more general analysis of remotely sensed data are introduced. The emphasis is on multidimensional image analysis (e.g. multispectral, polarimetric, multidate) and includes issues such as image registration and the use of geographic information systems (GIS) to support image analysis. Finally, based on the previous treatment, the parameters and processes governing spatial, spectral and radiometric image fidelity are studied with an emphasis on how each step in the image chain impacts the final image or image product. (Prerequisite(s): 1051-719 – Radiometry). Credit 4 (W)
1051-762 Spectral Image Analysis
This course is focused on analysis of high dimensional remotely sensed data sets. It begins with a review of the properties of matter that control the spectral nature of reflected and emitted energy. It then introduces three mathematical ways to characterize spectral data (i.e. spectral features, multivariate statistics and spectral subspaces) and methods to perform initial analysis of spectral data to characterize and preprocess the data. These include noise characterization and mitigation, radiometric calibration, atmospheric compensation and dimensionality characterization and reduction. The remainder of the course focuses on spectral image analysis algorithms employing the three conceptual approaches to characterizing the data. These analytical tools are aimed at segmentation, subpixel or pixel unmixing approaches and target detection including treatment of signal processing theory and application. There is also a significant emphasis on incorporation of physics based algorithms into spectral image analysis. These algorithms attempt to extend the more data driven approaches by improving our characterization of target, backgrounds or the environment through knowledge of the physics governing the imaging process. (Prerequisite(s): 1051-719 – Radiometry and 1051-761 - Sensors and Radiometric Image Analysis). Class 4, Credit 4 (S)
1051-765 Remote Sensing Systems
This course is designed to draw on the student's knowledge of linear system theory, digital image processing, and noise concepts and apply it to an end-to-end system in an area associated with remote sensing. Generalized concepts from these fields will be focused to show how they can be applied to solve remote sensing image analysis and systems design and evaluation problems. An overriding objective is on the application of theory to practice. (Permission of instructor) Credit 4
1051-769 Spectral Methods and Instrumentation
This course examines methods and instrumentation for spectral sensing as applied to earth observation. Spectral dispersion and selection methods, with an emphasis on gratings, will be studied. The data collection and analysis procedures for spectral and radiometric calibration of a field spectroradiometer and an airborne spectral imager will be performed by the students in a research laboratory setting. Other methods and practices in spectral instrumentation for both passive and active sensing across the electromagnetic spectrum will be described. (1051-719 or permission of instuctor) Class 4, Credit 4 (offered alternate years) (F)
1051-775 Applied Colorimetry
This course covers the principles of color science including theory and application. Topics include CIE colorimetry, the use of linear algebra for color transformations, the Munsell color order system, metamerism, color inconstancy, history and theory of color tolerance equations and spaces, and an overview of color management. Also offered online. Class 4, Credit 4 (W)
1051-776 Color Modeling
This course explores mathematical techniques for predicting the spectral and colorimetric properties of colored materials and images from user-controlled drive signals. Color systems that are modeled include paint, computer-controlled LCD, continuous and halftone print ing, and spectral cameras. Accompanying laboratory stresses the use of multivariate statistics, nonlinear optimization, and technical writing. Final laboratory consists of a spectral-based color repro- duction system including input, display, and printed output. (1051-775). Class 4, Credit 4 (S)
1051-784 Digital Image Processing: Spatial Pattern Recognition
This course develops a fundamental understanding of adaptive pattern recognition and a basic working knowledge of techniques for use in a broad range of applications. Inherent in adaptive pattern recognition is the ability of the system to learn by supervised or unsupervised train- ing, or by competition within a changing environment. The effective- ness of the system depends upon it structure, adaptive properties and specifics of the application. Particular structures developed and analyzed include statistical PR, clustering systems, fuzzy clustering systems, multi-layered perceptrons (with a variety of weight training algorithms), and associative memory systems. The goal is to gain both a fundamental and working knowledge of each kind of system and the ability to make a good system selection when faced with a real application design. Also offered online. (1051-716, 718, 726, and 0304-834 or equivalent) Class 4, Credit 4 (W)1051-797 Principles of Computerized Tomographic Imaging
Image reconstruction from projections is introduced as a mathematical problem. Technique for reconstruction via Fourier domain is explained using Fourier slice theorem. Pure and filtered back-projection and iterative methods are introduced and analyzed. Algorithms for various techniques are developed and artifacts and noise in discrete case are considered. Applications to several medical imaging modalities (x-ray CT, PET, SPECT, MRI) are outlined, with brief consideration of the Physics involved in each case. Class 4, Credit 4 (S)1051-799 Independent StudyAn independent project in an area of imaging science not covered in the available courses. This project can be experimental research, literature review, or other appropriate work. This course requires a formal proposal and a faculty sponsor. Credit variable1051-812 Medical Imaging SystemsThis is an advanced graduate level course that describes existing medical imaging systems in terms familiar to imaging scientists and electrical engineers. These include impulse response, the transfer functions, and the signal to noise ratio. The course considers in detail, four different imaging modalities: conventional projection X-ray, CT, ultrasonic imaging, and magnetic resonance imaging. A complete system is examined piece by piece in terms of subsystems. Class 4, Credit 4 (S) 1051-816 Color SystemsThis course builds on the theory and concepts presented in the Color Reproduction and Color Modeling courses to cover the key techniques utilized in device-independent color imaging systems. Topics covered include: device calibration and characterization (input, output, display), device profiles, multidimensional look-up table construction, inversion, and interpolation, gamut mapping, appearance matching, and color-management systems. Also offered online. (1051 775, 726 or permission of instructor) Class 4, Credit 41051-840 MS Project PaperThe analysis and solution of Imaging Science Systems problems for students enrolled in Systems Capstone option. Credit 1 1051-890 Research and ThesisThesis (MS) or dissertation (Ph.D.) based on experimental data obtained by the candidate for an appropriate topic as arranged between the candidate and the research adviser. Credit variable 1051-999 Imaging Science Graduate Co-opCooperative work experience for graduate imaging science students. Credit 0
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