Catalog Description

Fundamentals of digital image processing hardware and software including digital image acquisition, image display, image enhancement, image transforms and segmentation.

Goals

To develop theoretic and algorithmic principles behind the acquisition, display, manipulation and processing of digital images. Practical laboratory tutorials and assignments will explore the methods used to digitize, transfer, display, organize, process and compare digital images and image sequences. Image processing software such as the IISS, Khoros and SGI ImageVision Library will be used to implement algorithms for and understand image file formats, representation and conversion methods, contrast enhancement by histogram manipulation, image statistics, image smoothing and sharpening using filtering algorithms, geometric transforms, frequency domain transform methods, inverse filtering, segmentation using region growing and boundary detection, etc.

Syllabus

1. Introduction to image and video processing, analysis and understanding with applications to computer vision and pattern recognition
2. Image perception, sampling and quantization
3. Image representation, modeling and display
4. Image enhancement: spatial domain vs frequency domain
5. Image processing software
6. Enhancement via point operations - contrast stretching, colormap look-up tables, clipping, thresholding, negation, gray-level slicing, bit-plane slicing, range compression, algebraic operators
7. Enhancement via histogram modeling - histogram modification, histogram equalization, histogram specification
8. Processing via algebraic operations - input and output histograms, sums and differences of images, averaging noisy images, background removal, change or motion detection
9. Processing via spatial operations - weighted local area smoothing or averaging, derivative filters (Roberts, Prewitt, Sobel, Kirsch, Laplacian), sharpening filters, unsharp masking, median filtering, gray level interpolation, spatial transformations, applications of geometric operations (cameral calibration, image registration, map projection, morphing)
10. Linear systems theory and 2-D convolution for image processing
11. Frequency domain approach and the 2-D Fourier transform
12. Discrete Fourier Transform and the FFT
13. Discrete image transforms - Discrete Cosine Transform, Eigenvector-based Transforms
14. Image restoration, inverse filtering and deconvolution
15. Hough Transform
16. Image segmentation via optimal histogram thresholding methods, connected components
17. Image and region statistics
18. Mathematical morphology
19. Texture analysis
20. Color models and multispectral images

Prerequisites (preferred)

• CS 4050/303: Design and Analysis of Algorithms I
• Statistics 4710/320: Introduction to Mathematical Statistics
• Senior standing or Graduate student

• CS 3530/253 Unix Operating System (Linux, SGI IRIX, etc.)
  
• C or C++ programming languages and object oriented design
  
• Matrix Algebra, Fourier Transforms

Required Text

• Digital Image Processing, 2nd Edition, by R.C.Gonzalez and R.E.Woods, Prentice Hall, 2002.

Other Texts and Sources

• CMU Computer Vision Resource
• USC Annotated IP and Vision Bibliography
• Fundamentals of Digital Image Processing, by Anil K. Jain, Prentice-Hall, 1989. An overview of many topics including image transforms, stochastic models, image analysis, and image compression.
• Digital Image Processing by K. R. Castleman, Prentice Hall, 2nd Ed., 1996. In addition to covering many areas of image processing includes wavelet transforms, pattern recognition, classification, and map projections.
• Digital Image Processing by W.K Pratt, John Wiley, 2nd Ed. , New York, 1991. Detailed mathematical treatment of image processing and image analysis.
• Digital Picture Processing by A. Rosenfeld and A.C. Kak, Academic Press, London, Vol 1 & Vol 2, 1982. One of the earliest books covering an extensive range of topics in imaging including data structures, image matching, segmentation, probabilistic relaxation, syntactic methods, restoration, etc.

Additional References

• IEEE Transactions on Image Processing
• CVGIP: Image Understanding
• CVGIP: Image Processing and Graphics
• IEEE Transactions on Pattern Analysis and Machine Intelligence