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Course Schedule of Topics
1. Overview (1 lecture)
2. Playing With Images (2 lectures)
· Representing lines, rectangles, and their translations and rotations.
· Extracting a region and moving it to a new location
· Looking at intensity along a line
· Enlarging and shrinking regions
· Thresholding a region
· Histogram of intensity
· Histogram-based segmentation
3. MATLAB (1 lecture)
How to use MATLAB and the image processing toolbox
4. Cameras and Image Formation (3 lectures)
· The thin lens
· Basic radiometry
· The perspective camera
· Camera parameters - intrinsic and extrinsic
5. Color and Various Image Sensors (1 lecture)
· Color
· Range sensors
· MRI, CT, Ultrasound, PET
6. Introduction to Statistical Image Processing (7 lectures)
· Image noise and averaging
· General convolution filtering
· Optimal signal or object detection in an image
· Edges - how to extract them from messy images
· Canny edge detection
· Deformable boundary curve and surface estimation in noisy 2D and 3D images
· Image segmentation
7. Estimation of other image features (3 lectures)
· Conics - least squares fitting of lines and conics to noisy data
· Hough Transform - for finding lines in images
8. Invariance and Invariant Features under Position and Viewpoint Changes (2 Lectures)
· Length, area, volume
· Axes of conics
· Moment invariants
· Invariants for groups of primitives
9. Fourier Analysis and Optimal Linear Filtering (9 lectures)
· Sampling Theorem
· DFT (Discrete Fourier Transform)
· Circular discrete convolution
· 2-Dimensional DFT
· Image Compression
· Wavelets
· Optimal (Least Squares) filtering
· Weiner filtering
· Texture modeling and detection
· Change detection for segmenting video clips
10. Nonlinear Filtering (3 lectures)
· Morphology
· Skeletons
11. 3D Surface Reconstruction by Stereo (3 lectures)
· Camera calibration: Estimating camera parameters
· Estimating 3D points, lines, planes, other primitives
