Computational Photography

Semester: Spring 2009

Course code: G22.3033-003

Instructor: Rob Fergus     

Previous editions of the course: G22.3033-006: Spring 2008 Link

Course description:

Computational Photography is an exciting new area at the intersection of Computer Graphics and Computer Vision. Through the use of computation, its goal is to move beyond the limitations of conventional photography to produce enhanced and novel imagery of the world around us. The main focus of the course will be on software-based methods for producing visually compelling pictures. However, it will also cover novel camera designs, for which computation is integral to their operation. The course will explain the principles behind many of the advanced tools that can be found in Adobe Photoshop, although the use of this package itself is outside the scope of the course. The course will be suitable for advanced undergraduates, masters and PhD students. A reasonable knowledge of linear algebra is required and familiarity with Matlab is desirable. Assessment will be through coursework and a course project.


1. Introduction, image formation and cameras.
2. Sampling & reconstruction, frequency domain.
3. Wavelets, natural scene statistics.
4. Color, demosaicing.
5. Image processing.
6. Image blending & compositing.
7. Image warping & morphing.
8. Non-parametric methods.
9. Video.
10. Deconvolution & deblurring.
11. Depth & defocus.
12. Matting.
13. Lighfields.
14. Project presentations.