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All core courses are offered at least once each year. Most other courses are offered either once a year or every other year. 1051-706,707,708 Imaging Science Seminar
The course introduces the student to the historical context from which the field of Imaging Science has evolved. It proceeds to define the fundamental scientific principles on which the science is based and to expose the student to the technologies and directions that encompass the field. This course is intended to set the framework for graduate study in Imaging Science and to provide the non-image scientist with a non-quantitative survey of the field.
Credit 1
This course provides the student with a basic understanding of the scientific principles associated with electromagnetic radiation propagation, image capture and formation, and image processing used to reproduce or display images. An end-to-end treatment of an imaging system shall be employed to illustrate the interrelationships among the concepts introduced throughout the course. System analyses include the use of modeling concepts and image quality metrics to demonstrate how the concepts developed in Linear Image Mathematics can be used in concert with concepts in this course to describe and assess a simple imaging system.
Credit 4
This course continues the development of basic understanding of scientific principles associated with image capture, formation, and image processing used to reproduce or display images. An end-to-end treatment of an imaging system shall be employed to illustrate the interrelationships among the concepts introduced throughout the course. System analyses include the use of modeling concepts and image quality metrics to demonstrate how the concepts developed in Linear Image Mathematics can be used in concert with concepts in this course to describe and assess a simple imaging system.
Credit 4
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.
Credit 4
This 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.
Credit 4
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 is discussed first, followed by development and use of the convolution integral. This is followed 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. Image sampling and quantization is introduced and discrete convolution and Fourier transform is considered. 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.
Credit 4
This course continues the development of mathematical methods required to describe continuous and discrete linear systems that was begun in 1051-716, with emphasis placed on the use of discrete models of imaging systems. The various types and effects of quantization are considered first, followed by discussions of common means to process sampled and quantized images. The use of linear models of imaging systems is considered, including the discussion of the valid limiting cases of optical imaging in coherent and incoherent light. The course concludes with discussions of various applications of the mathematical models.
Credit 4
This three quarter laboratory is designed to parallel the Basic Principles of Imaging Science I, II, and Noise and Random Processes core requirements. It provides hands-on experience with imaging materials and devices, digital imaging techniques, electro-optical devices, and other imaging modalities. It is intended to reinforce course work and provide the student exposure to, and facility with, a broad variety of instrumentation and analytical methods. In addition, statistical methods of data analysis will be introduced and utilized.
Credit 1
This three quarter laboratory sequence is designed to parallel the Basic Principles of Imaging Science I, II, and Noise and Random Processes core requirements. It provides hands-on experience with imaging materials and devices, digital imaging techniques, electro-optical devices, and other imaging modalities. It is intended to reinforce course work and provide the student exposure to, and facility with, a broad variety of instrumentation and analytical methods. In addition, statistical methods of data analysis will be introduced and utilized.
Credit 1
This three quarter laboratory sequence is designed to parallel the Basic Principles of Imaging Science I, II, and Noise and Random Processes core requirements. It provides hands-on experience with imaging materials and devices, digital imaging techniques, electro-optical devices, and other imaging modalities. It is intended to reinforce course work and provide the student exposure to, and facility with, a broad variety of instrumentation and analytical methods. In addition, statistical methods of data analysis will be introduced and utilized.
Credit 1
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.
Credit 4
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.
Credit 4
This course provides the student with a basic understanding of the principles of chemical imaging. The physical and chemical principles required for studying chemical imaging are reviewed. The phenomenon and mechanism of reciprocity law failure are illustrated. Emphasis is on relating the underlying principles of physics and chemistry to the metrics of system performance. Technologies to be covered include ink jet and thermal printing.
Credit 4
A continuation of 1051-731 providing the student with a basic understanding of the principles of chemical imaging. Emphasis is on relating the underlying principles of physics and chemistry to the metrics of system performance. Chemical imaging technologies to be covered include electrophotographic, silver halide, and polymer. Spatial properties of chemical images are related to their underlying physics and chemistry.
Credit 4
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.
Credit 4
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.
Credit 4
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.
Credit 4
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.
Credit 4
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.
Credit 4
This course will be divided into two parts. Half will focus on hyperspectral imaging. It will start with the physical and chemical phenomena that cause spectral signatures and trace spectral imaging through sensing by imaging spectrometers and analysis with specialized algorithms for handling spectrally rich data. The other half of the course will have more of a seminar flavor and will focus on Synthetic Image Generation (SIG). Several SIG models will be reviewed by the class and compared to the DIRSIG model which will be treated in detail as a point of reference for the other models. A particular emphasis will be placed on the potential for using SIG to model the hyperspectral phenomena.
Credit 4
An introduction to materials and processes in electrophotography. Topics include an historical development of electrostatic and electrophotographic imaging, surface deformation imaging, and current topics in electrophotographic and related processes.
Credit 4
This course describes the physical basis for field variation electrophotography, and the fundamentals of xerographic system design and analysis. Topics covered include calculation of development fields, the mathematical and physical basis for viscosity-controlled and adhesion-controlled development, the physical basis for charging and discharging photoconductors, and system optimization of the xerographic process.
Credit 4
Basic principles and techniques in engineering design and analysis of electrophotographic copiers, input scanners, raster output scanners, and other solid state electronic printing devices. Emphasis will be given to such topics as reliability, systems optimization, quality control, and print and copy quality.
Credit 4
An introduction to radiometric concepts as they relate to remote sensing. The emphasis is on aerial and satellite imaging systems operating from 0.4 - 20 µm. After a brief review of the field, the basic radiometry concepts needed for remote sensing are introduced and a governing equation for radiance reaching the sensor is carefully derived.
Credit 4
The problem of inverting recorded image data to surface reflectance on temperature values is treated using a variety of techniques, including the use of ground truth, "in scene" methods, and radiation propagation models. Multispectral digital image processing methods are introduced and their utility in various remote sensing applications considered. The potential for including multiple sources of data in image analysis is treated through consideration of multispectral image data fusion and the use of geographic information systems. The laboratory involves hands-on image data processing employing the techniques introduced in 761 and 762.
Credit 4
Analysis of digital remotely sensed images is treated with emphasis on multispectral analysis techniques. This includes consideration of multivariate discriminate analysis and principal components for material identification and analysis. Special topics such as radar, Fraunhofer line discriminator, hierarchical classifiers will also be treated.
Credit 4
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.
Credit 4
A comprehensive study of the science of imaging with silver halide materials. Includes materials preparation and their physical and chemical properties, mechanisms and efficiency of image recording, and reciprocity law failure measurement and mechanisms. The course will focus on correlations between events at the atomic and molecular level and their manifestation at the macroscopic level. (Offered in alternate years)
Credit 4
A continuation of the comprehensive study of the science of imaging with silver halide materials. Includes mechanisms and procedures of chemical sensitization, dopants, and spectral sensitization, and image detection and enhancement. This course will focus on correlations between events at the atomic and molecular level and their manifestation at the macroscopic level. (Offered in alternate years)
Credit 4
A comprehensive study of the application of silver halides in imaging systems. The emphasis is on how the materials properties of silver halides influence the properties of the imaging system such as sensitivity, reciprocity failure, curve shape, color and tone reproduction, granularity, sharpness, resolution, and processability. (Offered in alternate years)
Credit 4
This course provides an overview of the human visual system and psychophysical techniques used to investigate it. The optical, sensory, and neural aspects of vision and image quality are treated. Topics include color vision, adaptation, sensor response functions, neural networks, and an introduction to electro-optical and computational analogs.
Credit 4
An introduction to the measurement and specification of color. The CIE system of colorimetry is presented with an emphasis on its practical application to common problems in quality control, reproduction, and imaging. Topics: color perception, photometry, trichromatic theory, color matching mathematics, obtaining colorimetric data through measurement, color quality spaces, deriving industrial tolerances, and an introduction to device independent color.
Credit 4
This course explores mathematical techniques for predicting the coloring of absorptive systems including polymers, textiles, paper (impact and non-impact), and coatings, and the modeling of additive systems such as self-luminous displays. Emphasis is placed on Kubelka-Munk turbid media theory for opaque and translucent systems and on Grassmann's laws for additive systems. Accompanying laboratory stresses the use of commercial computer colorant formulation systems and the use of multivariate sttistics to model colorant behavior.
Credit 4
This course provides an in-depth look at various pieces of instrumentation used in many low light imaging applications with emphasis on astronomical requirements. Aspects of hardware, systems analysis, and performance calculation will be covered.
Credit 4
After a brief review of 2-dimensional signal processing, the course discusses the processing of images on a computer. It includes methods of contrast manipulation, image smoothing, and image sharpening using a variety of linear and non-linear methods. Also discussed are methods of edge and line enhancement and detection, followed by techniques of image segmentation. The course concludes with a discussion of image degradation models and image restoration.
Credit 4
This course develops a fundamental understanding of adaptive pattern recognition and develops a basic working knowledge of techniques that can be used in a broad range of applications. Inherent in adaptive pattern recognition is the ability of the system to learn by supervised or unsupervised training, or by competition within a changing environment. The effectiveness of the system depends upon its structure, adaptive properties and specifics of the application. Particular structures that are 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.
Credit 4
Image reconstruction from projections is introduced a mathematical problem. Technique for reconstruction via Fourier domain is explained using Fourier slice theorem. Simple and Filtered Backprojection and iterative methods are analyzed. Algorithms for various techniques are developed and artifacts and noise in discrete case are considered. Applications to several medical imaging modalities are outlined, with brief consideration of the physics of imaging involved in each case.
Credit 4
This course covers several advanced aspects of optics and imaging that are not included in other regular course offerings. Topics vary every year. The course may be taken more than once. Student participation includes presentations to the class on agreed upon topics.
Credit 1
This course covers several advanced aspects of optics and imaging that are not included in other regular course offerings. Topics vary every year. The course may be taken more than once. Student participation includes presentations to the class on agreed upon topics.
Credit 1
This course covers several advanced aspects of optics and imaging that are not included in other regular course offerings. Topics vary every year. The course may be taken more than once. Student participation includes presentations to the class on agreed upon topics.
Credit 1
The focus is on concepts of "Imaging Systems" and system's Image Quality. Metrics of Image Quality (IQ) metrics of concern in systems which are not discussed elsewhere in the curriculum. These will include concepts such as costs, reliability, and permanence. Two particular types of imaging systems will be covered in detail. The first, designated the "Internal Imaging System", focuses on strategies for the design and quality optimization of components internal to individual technologies. The second type of imaging system, designated the "External Imaging System", focuses on strategies for the design and quality optimization of components of an imaging chain.
Credit 4
This 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, three different imaging modalities: Conventional projection X-Ray radiography and X-Ray CT, ultrasonic imaging, and magnetic resonance imaging. A complete system is examined piece by piece in terms of subsystems.
Credit 4
This 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.
Credit 4
The analysis and solution of Imaging Science Systems problems for students enrolled in Systems Capstone option.
Credit 1
Thesis (M.S.) or dissertation (Ph.D.) based on experimental data obtained by the candidate for an appropriate topic as arranged between the candidate and the research advisor.
Credit 6 minimum (M.S.)
Credit 24 minimum (Ph.D.)
Any non-1051 courses must be approved, in writing, by the Graduate Coordinator(s). The student must submit a complete study plan. Once the plan is approved, it will be placed in the student's folder to be used for degree certification. Any deviations from the plan must also receive prior approval by the Graduate Coordinator(s).
Independent Study provides qualified students the opportunity to engage in a learning experience outside of the traditional classroom setting. Through Independent Study, interested students can, with the supervision of a faculty sponsor, learn through the initiation of a project or research area that ranges beyond the normal course offerings of CIS. To provide real learning, the Independent Study must be well planned. A written proposal which includes the objectives, methods of research and criteria for evaluation must be submitted to the sponsoring faculty member before registration can be processed. The proposal must also be signed by the coordinator of the appropriate degree program. Independent Study proposal forms are available from the Academic Student Records Office, or Program Coordinator. |