Image Processing Basics

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Related lectures (31)

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Image Processing I: Correlation Measures and Matched Filtering

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

Reconstructing Color Images: Techniques and Applications

Covers techniques for reconstructing color images using optical detection and artificial intelligence to enhance image quality and reduce noise.

Digital Image Correlation: Practical

Focuses on the practical application of Digital Image Correlation for civil engineers, covering measuring displacement fields and computing strain fields.

Nonlinear SVM: Kernels and Dual Optimization

Explores transforming data with nonlinear maps, kernels, dual optimization, and interpreting SVM results.

Feature Maps and Kernels

Covers feature maps, Representer theorem, kernels, and RKHS in machine learning.

Linear Transformations: Matrices and Kernels

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Kernel Regression: K-nearest Neighbors

Covers the concept of kernel regression and K-nearest neighbors for making data linearly separable.

Edge Detection: Deep Learning Insights

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

Seam Carving: Energy Minimization

Introduces seam carving for image resizing through energy minimization techniques.

Directional Image Analysis: Steerable Filters

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