Lecture Videos :
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Introduction to Biomedical Signal Analysis
by Prof. Jiri Jan
Click on Computer (
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Welcome |
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Introduction to Selected Concepts Overview of the lectures (No voice in this lecture) Part I: Images as Multidimensional Signals Analogue (Continuous) Images Images as Signals Some 2D Elementary Signals Harmonic 2D Signals 2D systems – Description in the Original Domain |
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Classification of 2D systems 2D Linear Systems Physical Interpretation of the Superposition Integral 2D Fourier Transform Definition of the Forward Transform Definition of the 2D Inverse Transform |
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Physical Interpretation of the 2D FT Basic Properties of the 2D FT 2D Systems – Description in the Frequency Domain Stochastic Images |
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Digital Image Representation Grey-Scale Histogram Reconstruction of Continuous Images from Samples Discrete 2D Operators Discrete 2D Linear Operators Separable Linear Operators |
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Local Operators Convolution Operators Nonlinear Operators Order Statistics Operators |
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Part III: Reconstruction of Images from Tomographic Projections Representation of an Image by Projection Radon Transform Algebraic Methods of Reconstruction Principle of the Iterative Solution of the Equations |
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Reconstruction via Frequency Domain Reconstruction Based on the Slice Theorem Filtered Back Projection |
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Steps of the FBP Reconstruction in Discrete Environment Reconstruction from Fan Projections Geometry of Measurement Conversation into Parallel Projections Weighted and Filtered Back Projection |
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Part II: Image Enhancement Contrast Transforms Piecewise Linear Contrast Transform Histogram Equalization |
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Pseudo-Coloring Image Sharpening and Edge Enhancement Difference Approximations of Derivatives in Discrete Environment Approximations of Isotropic Operators Sharpening Operators Sharpening via Frequency Domain Adaptive Sharpening |
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Noise Suppression Classification of Noise Suppression of Narrow-Band Noise Suppression of Wideband "Grey" Noise "Smart" Smoothing Suppression of impulse Noise Detection of False Pixels Suppression of Impulse Noise by Median Filtering |
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