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Course Criteria
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4.00 Credits
This course will introduce the student to the IDL environment as a data visualization tool and a programming language. The student will learn the various capabilities of the package and how they can rapidly prototype solutions to various science and engineering problems. As these solutions are developed, fundamental concepts of programming and data structures will be introduced. Programming assignments will include fundamental imaging related problems and will work with scalar, vector and array processes. This course will emphasize the need for concrete problem defi nition, problem decomposition into smaller sub-problems, implementation/testing, and presentation/ documentation of the algorithm and results. (Algebra and trigonometry) Class 4, Credit 4 (F)
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2.00 Credits
An exploration of the fundamentals of imaging science and the imaging systems of the past, present and future. Imaging systems studied include the human visual system, consumer and entertainment applications (e.g., traditional and digital photography, television, digital television and HDTV, virtual reality); medical applications (e.g., X-ray, ultrasound, MRI); business/document applications (e.g., impact and non-impact printing, scanners, printers, fax machines, copiers); and systems used in remote sensing and astronomy (e.g., night-vision systems, ground- and satellite-based observatories). The laboratory component includes experiments related to the principles and theories discussed in the corresponding lecture. Laboratory experiments give students experience with many imaging systems and exposure to the underlying scientifi c principles. (Competency in algebra) Class 3, Lab 2, Credit 4 (F, W)
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2.00 Credits
Familiarizes students with the goals and techniques of astronomical imaging. The broad nature of astronomical sources will be outlined in terms of requirements on astronomical imaging systems. These requirements are then investigated in the context of the astronomical imaging chain. Imaging chains in the optical, X-ray, and/or radio wavelength regimes will be studied in detail as time permits. Laboratory assignments will range from construction and characterization of a hand-held telescope to analysis of images collected at the RIT Observatory. (1051-215 or permission of instructor) Class 3, Lab 2, Credit 4 (W)
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3.00 Credits
Topics of special interest, varying from quarter to quarter, selected from the fi eld of imaging science and not currently offered in the curriculum. Specifi c topics are announced in advance. (Not offered every quarter, consult director of the Center for Imaging Science) Class variable, Credit variable
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3.00 Credits
This course provides a framework for the study of imaging science in the remainder of the imaging science curriculum. Elements of imaging science taxonomy, including the imaging chain, image analysis and imaging systems characterization are introduced or reviewed. Practical examples are drawn from familiar imaging systems such as digital and fi lm still cameras, LCD displays, NTSC video, etc., are introduced and selected systems are studied in depth. Current events in the development or use of imaging science will be incorporated at the discretion of the instructor to reinforce understanding of the structure of the fi eld of imaging science. The student will master basic laboratory skills in the use of still and video cameras, including effects of and control of illumination, exposure, focus and depth of fi eld, focal length, dark and fl at fi eld calibration. (1051-204, 1017-311, or equivalent) Class 3, Lab 3, Credit 4 (F)
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3.00 Credits
This course introduces the description of optical imaging systems based on the ray model of light. Topics include refraction, refl ection, imaging with lenses, stops and pupils, and optical system design using computer software. (1017-313) Class 3, Lab 3, Credit 4 (W)
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4.00 Credits
Fundamental aspects of the interaction of electromagnetic radiation and materials. The course is designed to provide students with an understanding of the physical mechanisms underlying instruments used to detect, measure, and image electromagnetic energy (CCDs, silver halide fi lm, OPC, vidicon, etc.). Basic concepts of quantum theory, atomic structure and the particle/wave duality of light and matter are introduced. Electronic transitions in materials and the physical and chemical results of light absorption are explored, with practical examples in image detection. Applications in detector sensitivity, spectroscopy, human vision, and colorimetry will be touched on. (1016-283, 1017-314) Class 4, Credit 4 (F)
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4.00 Credits
This course applies the concepts of complex numbers, vectors, and matrices to represent models of discrete linear imaging systems. Representations of discrete imaging systems are considered and the representation in the frequency domain is derived via the discrete Fourier transform. The continuous Fourier transform is introduced. (1016-305) Class 4, Credit 4 (W)
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4.00 Credits
The fi nal "component" in many imaging systems is visual perception. Thehuman visual system can also be considered as an imaging system itself; arguably the most complex system, from visual optics through high-level cortical processing such as the perception of depth and motion. An understanding of the characteristics and limitations of the visual system aids in designing and evaluating imaging systems. Unlike other elements of imaging systems, it is diffi cult or impossible to get objective measures of visual perception; psychophysics provides tools for measuring perceptual mechanisms. This course presents an overview of the organization and function of the human visual system and some of the psychophysical techniques used to study visual perception. (1051-300 or permission of instructor) Class 4, Credit 4 (W)
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4.00 Credits
This course is an introduction to the basic concepts of digital image processing. The student will be exposed to image capture and image formation methodologies, sampling and quantization concepts, statistical descriptors and enhancement techniques based upon the image histogram, point processing, neighborhood processing, and global processing techniques based upon kernel operations and discrete convolutions as well as the frequency domain equivalents, geometrical operations for scale and rotation, and greylevel resampling techniques. Emphasis is placed on applications and effi cient algorithmic implementation using the IDL programming language. (1016-283, 1016-305, 1051-211 or equivalent) Class 4, Credit 4 (F)
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