DIP Lecture 17: Image restoration and the Wiener filter

ECSE-4540 Intro to Digital Image Processing
Rich Radke, Rensselaer Polytechnic Institute
Lecture 17: Image restoration and the Wiener filter (4/9/15)
0:00:02 Image restoration overview: subjective vs. objective
0:02:19 Image degradation model: blur + noise
0:05:24 The no-blur case (H = identity)
0:08:33 Estimating the noise model
0:09:19 Common noise models
0:12:44 Special case: periodic noise
0:15:50 Removing periodic noise with a notch filter
0:18:50 Estimating i.i.d. noise
0:24:54 Removing noise
0:29:07 Adaptive filters
0:35:28 Noise removal example
0:41:44 Dealing with blur/degradation
0:44:06 Estimating the blur H
0:52:17 The inverse filter (usually bad)
0:57:39 The modified inverse filter
0:59:08 The Wiener filter
1:06:50 Wiener filtering example
1:10:43 Modern research on removing camera shake from digital images
Follows Sections 5.1-5.8 of the textbook (Gonzalez and Woods, 3rd ed.).
The periodic noise image is from the nice page on image restoration at miac.unibas.ch...