CLASS INFORMATION:

Course Description: The plethora of images on the internet, the ubiquitous access to digital cameras and personal computers have spurred an interest in computational imaging techniques that organize images and enhance or extend the capabilities of digital cameras. Computational photography refers to analysis, manipulation and synthesis of images using numerical algorithms. It combines methodologies from image processing, computer vision, computer graphics and photography.

Prerequisites: Linear Algebra, Probability, or consent of the instructor.

Grading:

			Option A	Option B
	Problem Sets (~6) with lab exercises in Matlab. Problem sets may be discussed, but all written work and coding must be done individually.		30%	50%
	Exams: One take-home exams.              (Take-home exam may not be discussed.)		30%	0%
	Final Project:   An original implementation of a new or published idea A detailed empirical evaluation of an existing implementation of one or more methods   Project proposal not longer than two pages must be submitted and approved before the end of October.		30%	40%
	Class Participation:		10%	10%