Lectures related to Image Processing Labs with Jupyter Notebooks

Image Processing I: Segmentation and Thresholding

Explores image segmentation, thresholding techniques, texture segmentation, and connected-component labeling in image processing.

Image Processing I: Edge Detection and Texture Analysis

Covers edge detection, texture analysis, Canny's algorithm, filterbanks, and segmentation techniques.

Principal Component Analysis: Eigenfaces

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

Notation and key concepts

Covers the notation and key concepts related to digital images and 2D signal representations.

Image Processing Basics

Introduces image processing basics in Python, covering manipulation, grayscale conversion, edge detection, and convolution with kernels.

Image Processing II: B-spline Properties and Gradient Operators

Explores B-spline properties, gradient operators, interpolation, and differentiation filters in image processing.

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.