COURSE DESCRIPTION
We cover standard theoretical aspects of image
processing and coding.
Mathematical preliminaries are
considered first.
Applications are woven in, both in class and in the Lab experiments.
We will use experiments from previous Image Processing Labs (Fall 2003)
as also from the recent MathWorks Image Processing course Labs.
SYLLABUS
I. Two-dimensional linear discrete systems
(3)
Review of Fourier and z-Transforms,
stochastic processes, correlation, matrix operations
II. Image Transforms (4)
Orthogonal transforms, 2-D DFT, DCT,
DST, Karhunen-Loeve transform, 2-D Filters
III. Image Enhancement, Restoration (4)
Point processing, computing derivatives and smoothing,
Optimal filters, Wiener filters
IV. Working with images in MATLAB (2)
Binary, Intensity, Indexed, RGB images, Calculating image statistics
V. Applying Image Enhancement Techniques (4)
Histogram equalization techniques, Arithmetic point operations, Correcting image alignment
VI. Filtering Images (4)
Block processing, Convolution and Correlation, Spatial domain filters, Frequency domain filters
V11. Applying Image Restoration Techniques (3)
Modelling Noise, Denoising, Deblurring
VIII. Extracting Features Using Segmentation and Edge Detection (3)
Edge detection. Canny, Laplacian, Regularization
IX. Image Coding and Compression(4)
Quantization, Companding, Vector Quantization
TEXTS(Fall 2003)
Fundamentals of Digital Image Processing,
A.K.Jain, Prentice-Hall, 1989. Chs:1,2,4,5,6,7,11
K.R.Castleman, Prentice-Hall, 1996. Chs:11
O.Faugeras, Three-Dimensional Computer Vision, MIT Press, 1999.
Ch:4
{optional text}
MATLAB Image Processing ToolBox User's Guide
Instructor
Gagan Mirchandani, 355 Votey, 6-4587
Class times:12:30-1:45 p.m. Tue., Thu.
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