Image Filtering in Computer Vision - Part II - Lecture 5

Explore advanced image filtering techniques in this comprehensive computer vision lecture. Delve into mathematical concepts like derivatives, mean, and weighted mean, with practical examples. Learn about Gaussian smoothing, box filters, Sobel filters, and their properties. Discover how to handle Gaussian noise and apply median filters effectively. Examine the intricacies of Gaussian filters and padded edges. This lecture is part of the CAP5415 Computer Vision course at the University of Central Florida, covering essential topics in computer vision, machine learning, and deep learning for AI applications.

Introduction
Derivative
Derivative Example
Question
Mean and Weighted Mean
Examples
Gaussian smoothing
Gaussian noise
Box filter
Box filter example
Sobel filter
Filter properties
Medium filter
Median filter
Gaussian filter
Padded edges