Image Processing with Elements of Learning

Catalog description

This class will provide the students with an introduction to image processing, with applications to medical, urban agricultural and satellite images. Students will learn methods for 2D image enhancement, sharpening, blurring, noise detection, modeling and cleaning, as well as edge detection in gray level images. The methods students will be able to implement include local statistics, Laplacian and Gradient operators, Fourier transforms and the Fast Fourier Transform. Further, the class will introduce basic elements of convolutional neural networks to learn noise and its cleaning. At the end of the class the students will know which gray level image methods apply to color images. The students will develop skills in programming, reporting and presenting advanced method from the field. Prerequisites: CSCI 513 or CSCI 515 . Crosslisted with: MATH 563 .