Syllabus of lectures
Mathematical preliminaries of digital image processing: The space of image signals. Linearity and shift invariance of operators. Dirac delta function and its properties. Convolution. Discrete convolution. Applications of convolution in digital image processing.
Image transforms. The Fourier transform, discrete Fourier transform, cosine transform. Properties of Fourier transform. Fast Fourier transform. Modifying the frequency spectrum of images.
Wavelet transforms. Applications in digital image processing.
Compression of images: JPEG compression, MPEG compression of image sequences, Fractal compression.
Sampling and reconstructing the images. Aliasing. Quantization.
Geometrical transformations of images. Morphing and warping. Transformations of brightness.
Filtering. Recursive and non-recursive filtering. Non-recursive filter design.
Random fields and stochastic processes and their applications in digital image processing. Wiener filter.
Morphological image processing.
Methods of image segmentation. Thresholding. Optimal threshold selection. Image segmentaion based on region growing and splitting. Detecting edges in images. Gradient, and zero-crossing methods. Canny edge detector. Edge linking. Detecting feature points (corners).
Measuring objects. Selection and computation of features for pattern recognition.
Pattern recognition based on classification. Discriminant functions and etalons. Probablistic approach to determining the discriminant functions. Using neural networks for pattern recognition.
Reconstructing a scene from its two or more images. Absolute and relative camera calibration and reconstruction.
Analysis of time-varying images. Tracking objects in image sequences.
Mathematical preliminaries of digital image processing: The space of image signals. Linearity and shift invariance of operators. Dirac delta function and its properties. Convolution. Discrete convolution. Applications of convolution in digital image processing.
Image transforms. The Fourier transform, discrete Fourier transform, cosine transform. Properties of Fourier transform. Fast Fourier transform. Modifying the frequency spectrum of images.
Wavelet transforms. Applications in digital image processing.
Compression of images: JPEG compression, MPEG compression of image sequences, Fractal compression.
Sampling and reconstructing the images. Aliasing. Quantization.
Geometrical transformations of images. Morphing and warping. Transformations of brightness.
Filtering. Recursive and non-recursive filtering. Non-recursive filter design.
Random fields and stochastic processes and their applications in digital image processing. Wiener filter.
Morphological image processing.
Methods of image segmentation. Thresholding. Optimal threshold selection. Image segmentaion based on region growing and splitting. Detecting edges in images. Gradient, and zero-crossing methods. Canny edge detector. Edge linking. Detecting feature points (corners).
Measuring objects. Selection and computation of features for pattern recognition.
Pattern recognition based on classification. Discriminant functions and etalons. Probablistic approach to determining the discriminant functions. Using neural networks for pattern recognition.
Reconstructing a scene from its two or more images. Absolute and relative camera calibration and reconstruction.
Analysis of time-varying images. Tracking objects in image sequences.