Name
Abstract | ||
|---|---|---|
Image deblurring to remove blur caused by camera shake has been intensively studied. Nevertheless, most methods are brittle and computationally expensive. In this paper we analyze multi-image approaches, which capture and combine multiple frames in order to make deblurring more robust and tractable. In particular, we compare the performance of two approaches: align-and-average and multi-image deconvolution. Our deconvolution is non-blind, using a blur model obtained from real camera motion as measured by a gyroscope. We show that in most situations such deconvolution outperforms align-and-average. We also show, perhaps surprisingly, that deconvolution does not benefit from increasing exposure time beyond a certain threshold. To demonstrate the effectiveness and efficiency of our method, we apply it to still-resolution imagery of natural scenes captured using a mobile camera with flexible camera control and an attached gyroscope. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/CVPR.2014.430 | CVPR |
Keywords | Field | DocType |
blur model,flexible camera control,image capture,mobile camera,align-and-average deconvolution,multi-image frame capture,image restoration,camera motion,deconvolution,cameras,camera shake,natural scenes,image deblurring,gyro-based multi-image deconvolution,gyroscopes,gyroscope,image motion analysis,kernel,psnr,mathematical model | Computer vision,Shake,Gyroscope,Deblurring,Pattern recognition,Computer science,Camera auto-calibration,Deconvolution,Camera resectioning,Artificial intelligence,Image restoration,Multi-image | Conference |
ISSN | Citations | PageRank |
1063-6919 | 12 | 0.60 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sung Hee Park | 1 | 116 | 10.11 |
| Marc Levoy | 2 | 10273 | 1073.33 |