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Superresolution imaging - from equations to mobile applications
Published on Jan 23, 20127043 Views
In the last five years we have witnessed a rapid improvement of methods that perform image restoration, such as, denoising, deconvolution and superresolution. We will provide a brief mathematical back
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Chapter list
Superresolution Imaging from Equations to Mobile Applications00:00
Superresolution - 100:16
Recalling Nyquist00:46
Nyquist Sampling01:28
Superresolution - 202:14
Traditional superresolution sub-Nyquist sampling02:30
Traditional superresolution03:07
Realistic Superresolution - 103:25
Multichannel Acquisition Model04:35
Realistic superresolution - 205:28
Superresolution & Blind Deconv.06:03
Alternating Minimization08:40
Variable Splitting09:14
Augmented Lagrangian Method09:52
Superresolution - 311:19
Space-variant Case - 112:37
Space-variant Case - 212:55
Interpolated / SR - 113:28
Interpolated / SR - 214:00
SR + Masking14:42
Camera-motion Blur15:03
Space-variant Superresolution - 115:43
Space-variant Superresolution - 217:42
Close-up17:56
Example - 118:23
Example - 219:23
Infrared video super-resolution - 119:42
Infrared video super-resolution - 220:51
Infrared video super-resolution - 321:12
Infrared video super-resolution - 421:56
"Blind" Deconvolution on Smartphones - 122:36
"Blind" Deconvolution on Smartphones - 223:28
"Blind" Deconvolution on Smartphones - 323:42
Wiener Filtering on Android Smartphones - 124:42
Wiener Filtering on Android Smartphones - 225:48
Thank You ...26:05