Directional Regularization for Image Reconstruction
Duration: 47 mins 25 secs
Share this media item:
Embed this media item:
Embed this media item:
About this item
| Description: |
Dong, Y
Thursday 7th September 2017 - 12:00 to 12:50 |
|---|
| Created: | 2017-09-08 08:54 |
|---|---|
| Collection: | Variational methods and effective algorithms for imaging and vision |
| Publisher: | Isaac Newton Institute |
| Copyright: | Dong, Y |
| Language: | eng (English) |
| Distribution: |
World
(downloadable)
|
| Explicit content: | No |
| Aspect Ratio: | 16:9 |
| Screencast: | No |
| Bumper: | UCS Default |
| Trailer: | UCS Default |
| Abstract: | In this talk, I will introduce a new directional regularization based on the total generalized variation (TGV), which is very useful for applications with strong directional information. I will show that it has the same essential properties as TGV. With automatic direction estimators, we demonstrate the improvement of using directional TGV compared to standard TGV. Numerical simulations are carried out for image restoration and computed tomography reconstruction. |
|---|---|
Available Formats
| Format | Quality | Bitrate | Size | |||
|---|---|---|---|---|---|---|
| MPEG-4 Video | 640x360 | 1.93 Mbits/sec | 689.10 MB | View | Download | |
| WebM | 640x360 | 628.62 kbits/sec | 218.39 MB | View | Download | |
| iPod Video | 480x270 | 521.96 kbits/sec | 181.27 MB | View | Download | |
| MP3 | 44100 Hz | 249.78 kbits/sec | 86.84 MB | Listen | Download | |
| Auto * | (Allows browser to choose a format it supports) | |||||