Lectures related to Pyramid (image processing)

Image Processing I: Correlation Measures and Matched Filtering

Explores correlation measures, matched filtering, and feature extraction in image processing.

Delineation: Techniques and Dynamics

Explores techniques for delineating objects in images, including dynamic programming and live wire methods.

Edge Detection: Deep Learning Insights

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Image Filtering: Classic Filters

Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.

HPC Infrastructure: Blue Brain Project

Explores the HPC infrastructure of the Blue Brain Project, including multi-compartment neuron refinement and large-scale data processing.

Topology: Polyhedral Products and Edge Detection

Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.

Directional Image Analysis: Steerable Filters

Explores directional image analysis and the implementation of steerable filters for edge and ridge detection.

Image Processing I: Dirac Impulse and Fourier Transform

Covers the abstract definition of Dirac impulse and its properties in image processing.

Image Processing I

Covers fundamental concepts in image processing, including preprocessing techniques and matching methods.

Image Processing I: Local Normalization and Morphological Operators

Introduces local normalization and morphological operators for shape analysis in image processing.

Image Processing I: Filters and Transformations

Explores moving average and exponential filters, Gaussian filtering, and linear scale-space concepts in image processing.

Principal Component Analysis: Eigenfaces

Covers the application of Principal Component Analysis in facial recognition using a famous faces dataset.

Directional Image Analysis and Processing

Delves into the mathematical foundations and importance of directional cues in image processing, exploring computational challenges and selectivity to orientation.

Introduction to Image Processing for Earth Observation

Covers the basics of image processing for Earth observation, including course objectives, administration details, interdisciplinary aspects, and key image processing concepts.

Image Processing: Neighborhood Averaging & Gaussian Smoothing

Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.

Image Processing I: Discrete Histogram Processing and Spatial Operators

Explores discrete histogram processing and spatial operators for image manipulation and noise reduction.

Edge and Contour

Covers edge and contour detection in images, including gradient-based methods, Laplacian operator, and more complex methods.

Gaussian and Polar Representations

Covers the concepts of complex numbers, orientation, and transformations.

Deep Learning: Exploring Vision and Language Transformers

Covers advanced transformer architectures in deep learning, focusing on Swin, HUBERT, and Flamingo models for multimodal applications.

Image Processing II: Bayesian Classification and Decision Making

Explores Bayesian classification, decision making, and pattern recognition applications in image processing.