EECS225B
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EECS 225B - Digital Image Processing
Subject
EECS
Course Number
225B
Department
Course Level
Graduate
Course Title
Digital Image Processing
Course Description
This course deals with computational methods as applied to digital imagery. It focuses on image sensing and acquisition, image sampling and quantization; spatial transformation, linear and nonlinear filtering; introduction to convolutional neural networks, and GANs; applications of deep learning methods to image processing problems; image enhancement, histogram equalization, image restoration, Weiner filtering, tomography, image reconstruction from projections and partial Fourier information, Radon transform, multiresolution analysis, continuous and discrete wavelet transform and computation, subband coding, image and video compression, sparse signal approximation, dictionary techniques, image and video compression standards, and more.
Minimum Units
3
Maximum Units
3
Grading Basis
Default Letter Grade; S/U Option
Instructors
Zakhor
Prerequisites
Basic knowledge of signals and systems, convolution, and Fourier Transform.
Repeat Rules
Course is not repeatable for credit.
Credit Restriction Courses. Students will receive no credit for this course after completing the course(s) below.
-
Credit Replacement Courses
-
Formats
Lecture
Term
Fall and Spring
Weeks
15 weeks
Weeks
15
Lecture Hours
3
Lecture Hours Min
3
Lecture Hours Max
3
Outside Work Hours
6
Outside Work Hours Min
6
Outside Work Hours Max
6