Syllabus
This is an advanced course on selected topics of image analysis.
Major attention is paid to image moments, moment-based features, wavelet transform, and to their applications in image processing, namely in object recognition, edge detection, noise removal, image registration, and image compression. Numerous practical applications and experimental results are presented in the lectures.
Topics:
- geometric moments, definitions and basic properties
- complex moments
- moment invariants to rotation and scaling
- moment invariants to affine transform
- moment invariants to convolution/blurring and combined invariants
- orthogonal polynomials and orthogonal moments (Legendre moments,
Fourier-Mellin moments, Zernike moments)
- discrete moments and their effective calculation
- introduction to wavelet transform (WT)
- edge and corner detection by means of the WT
- image denoising by means of the WT
- image registration by means of the WT
- wavelet-based image compression (block quantizing)
- other applications of the WT in image processing
Annotation
The course broadens topics of the course NPGR002: Digital Image Processing.
Main attention will be paid to several special functions and transformations (especially moment functions and wavelet transform) and their use in selected tasks of image processing - edge detection, noise removal, recognition of deformed objects, image registration, image compression, etc.
Both the theory and practical applications will be discussed.