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Welcome
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1 |
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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4 |
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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8 |
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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11
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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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