Provides a hands-on experience of image processing ranging from image formation, basic Fourier theory in multiple dimensions, machine learning theory as applied to image processing ranging from perceptions through transformers and LLM,s with applications, image denoising, image quality prediction, 3D-ranging by stereo, visual neuroscience of pictures and picture statistics. Homeworks are hands on applications of learned methods to real image processing tasks, and there is a semester-long project expected of each student or student team. Recommended prerequisite of ECEN 3810, Introduction to Probability Theory. Same as ECEN 4672.
