CS485/CS659 - Image Processing - Spring'2002

This course introduces basic concepts and methodologies for digital image processing, and focuses on material that is fundamental and has a broad scope of application.  Topics include contemporary developments in all mainstream areas of image processing e.g., image fundamentals, image enhancement in the spatial and frequency domains, restoration, color image processing, wavelets, image compression, morphology, segmentation, and image representation.

• R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2/e, Prentice Hall, 2002.
• B. Jähne, Digital Image Processing, 4/e, Springer, 1997.
• K. R. Castleman, Digital Image Processing, Prentice Hall, 1996.
• Selected papers.

1. Introduction
• Digital Image Fundamentals
• Image Formation
• Related Fields: PR, CV
• Readings - ch 1 & 2, handouts
2. Digital Image Processing Software
• Matlab
• Image Processing Toolbox
• Digital Image Formats
• Readings - handouts
3. Image Enhancement
• Graylevel Transformations
• Histogram Equalization
• Histogram Matching
• Readings - ch 3, handouts
4. Spatial Filtering
• Lowpass Filtering - Smoothing
• Highpass Filtering - Sharpening
• Readings - ch 3, handouts
5. Fourier Transform and Frequency Domain Filtering
• FT/FFT
• Lowpass Filtering - Smoothing
• Highpass Filtering - Sharpening
• Convolution, Correlation, and Autocorrelation Theorems
• Readings - ch 4, handouts
6. Image Restoration
• Image Denoising (spatial/frequency domain filtering)
• Degradation Modeling
• Inverse Filtering; Wiener Filtering
• Readings - ch 5, handouts
7. Line and Edge Detection
• Hough Transform
• Zero-Crossing, LOG
• Canny Edge Detector
• Readings - ch 10, handouts
8. Image Segmentation
• Otsu's Method
• Minimum Error Thresholding
• Adaptive Thresholding
• Readings - ch 10, handouts
9. Image Representation
• K-L Transform/PCA
• DCT
• Wavelet/Gabor
• Multiresolution Analysis
• Readings - ch 7, 11, handouts
10. Image Classification
• Bayes Classifier and MAP
• FLD/LDA; ICA
• Neural Networks
• SLT and SVM
• Readings - ch 12, handouts
11. Lossless Image Compression
• Redundancy
• Compression Models
• Shannon Entropy
• Huffman Coding; LZW Coding; Arithmetic Coding; Predictive Coding
• Readings - ch 8, handouts
12. Lossy Image Compression
• Image Compression (JPEG)
• Video Compression (MPEG)
• Audio Compression (MP3)
• Readings - ch 8, handouts
13. Color Image Processing
• Color Models/Spaces
• Pseudocolor Image Processing
• Fullcolor Image Processing
• Readings - ch 6, handouts
14. Morphological Image Processing and Digital Video Processing
• Readings - ch 9, handouts

Projects 40% (topics are related to our course Contents)

Homework 20% and Exams 30%

Class attendance 10%

• Face Detection Home Page
• The Face Recognition Home Page
• MATLAB
• Matlab Primer (Third Edition, By Kermit Sigmon - pdf file)
• Matlab Getting Started (copyright Mathworks - pdf file)
• Matlab Image Processing Toolbox User's Guide (copyright Mathworks - pdf file)
• Example images for project # 1

        image1 (binary file, image resolution 256 x 384)
        image2 (jpeg image)
        image3 (jpeg image)
        image4 (gif image)
        image5 (gif image)
• Example images for project # 2

        image1 (jpeg image, the original image for Topic 2)
        image2 (jpeg image, noise corrupted image for Topic 1)
        image3 (jpeg image, noise corrupted image for Topic 1)
        For either topic, you can use images downloaded from elsewhere.
• Example images for project # 3

        image1 (jpeg image)
        image2 (tiff image)
        You can use images downloaded from elsewhere.