Image Filtering, Convolution, and Edge Detection

Explore image processing techniques in this comprehensive lecture on image filtering, convolution, and edge detection. Delve into analytical and discrete derivatives, two-dimensional derivatives, and their application to images. Learn about correlation, convolution, and image noise before examining Gaussian filters and their 2D counterparts. Practice linear filtering techniques and discover image sharpening methods. Investigate the origins and characteristics of edges, including intensity profiles and the trade-off between smoothing and localization. Study various edge detection algorithms, such as Prewitt, Sobel, Marr-Hildreth, and Canny edge detectors. Understand the concept of zero crossings, separability of Gaussian and LOG filters, and evaluate edge quality. Gain valuable insights from Dr. Mubarak Shah of the University of Central Florida in this comprehensive 71-minute lecture on fundamental image processing concepts.