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Textbook
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Digital Image Processing, Gonzalez Rafeal, Prentice Hall, 2001
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References
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Digital Image Processing, William Pratt, John Wiley, 1991
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Fundamentals of Digital Image Processing, Anil K. Jain, Prentice Hall,
1989
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Digital Image Processing, Kenneth Castleman, Prentice Hall, 1996
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Digital Image Processing:Principles and Applications, Gregory Baxes,
John Wiley, 1994
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Principles of Digital Image Synthesis, Andrew S. Glassner, Morgan
Kaufman, 1995
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One-and Multidimensional Signal Proc.: Algorithms and Applications
in Image Proc., H. Schroder and H. Blume, John Wiley, 2000
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Course Description
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The course provides an introduction to basic concepts and methodologies
in image processing and develops the foundation for further study in
this diverse and rapidly evolving field. The topics range from enhancement
and restoration to image encoding, segmentation, description, recognition
and interpretation.
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Grading Policy
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Homework/Projects
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40 %
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Mid-term Exam
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25 %
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Final Exam
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35 %
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Total
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100 %
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Homework
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Homework will be assigned once a week and collected the following
week. Late submissions will not be accepted since the solutions will
be discussed in the class shortly thereafter.
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Software Requirement
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MATLAB/Simulink software will be used extensively in the course. The
software is available on most department laboratory machines, and student
copies can be borrowed from the ECE department for a small deposit. However,
other equivalent software can be used or the student can develop his/her
own software.
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Honor Code
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Students are expected to follow the ODU Honor Code for all assignments
and exams. Any violations will be dealt with strictly according to university
policy. However, this is also a course, which requires a lot of interaction,
and sharing of ideas is encouraged. But all work that you turn in with
your name on it should reflect your work, not someone else's. If at
any time you have a question about whether you are violating the Honor
Code, please ask me to make sure.
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Disabilities
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Students who have documented disabilities in accordance with university
guidelines will be provided appropriate opportunities if the documentation
is brought to the instructor's attention.
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Course Outline
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Introduction: Digital image representation, Fundamental steps
in image processing
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Digital Image Fundamentals: Elements of visual perception,
Image model, Sampling and quantization, Basic relationship between pixels,
Imaging geometry
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Image Transforms: Introduction to Fourier transform, Discrete
Fourier transform, Properties of two-dimensional Fourier transform,
Fast Fourier transform, Other separable transforms, Discrete cosine
transform, Discrete wavelet transform
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Image Enhancement: Enhancement by point processing, Histogram
processing, Spatial filtering, Enhancement in the frequency domain,
Homomorphic filtering, Color image processing
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Image Restoration: Degradation model, Interactive restoration,
Geometric transformations
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Image Compression: Fundamentals, Data redundancy, Fidelity
criteria, Image compression models, Elements of information theory,
Error-free compression, Variable length coding, Lossy compression, Transform
coding, Image compression standards
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Image Segmentation: Detection of discontinuities, Edge linking
and boundary detection, Thresholding, Region-oriented segmentation
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Representation and Description: Representation schemes, Polygonal
approximations, Signatures, Boundary descriptors, Shape numbers, Fourier
descriptors, Moments, Regional descriptors, Texture, Morphology, Dilation
and erosion, Hit-or-miss transform
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Recognition and Interpretation: Elements of image analysis,
Patterns and pattern classes, Decision-theoretic methods, Structural
methods, Interpretation
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