Abstract
Video camera is now commonly used and demand of capturing a single frame from video sequence is increasing. Since resolution of video camera is usually lower than digital camera and video data usually contains a many motion blur in the sequence, simple frame capture can produce only low quality image; image restoration technique is inevitably required. In this paper, we propose a method to restore a sharp and high-resolution image from a video sequence by motion deblur for each frame followed by super-resolution technique. Since the frame-rate of the video camera is high and variance of feature appearance in successive frames and motion of feature points are usually small, we can still estimate scene geometries from video data with blur. Therefore, by using such geometric information, we first apply motion deblur for each frame, and then, super-resolve the images from the deblurred image set. For better result, we also propose an adaptive super-resolution technique considering different defocus blur effects dependent on depth. Experimental results are shown to prove the strength of our method.
| Original language | English |
|---|---|
| Title of host publication | Computer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers |
| Pages | 127-140 |
| Number of pages | 14 |
| Edition | PART 4 |
| DOIs | |
| Publication status | Published - Mar 16 2011 |
| Externally published | Yes |
| Event | 10th Asian Conference on Computer Vision, ACCV 2010 - Queenstown, New Zealand Duration: Nov 8 2010 → Nov 12 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 4 |
| Volume | 6495 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 10th Asian Conference on Computer Vision, ACCV 2010 |
|---|---|
| Country | New Zealand |
| City | Queenstown |
| Period | 11/8/10 → 11/12/10 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
Video deblurring and super-resolution technique for multiple moving objects. / Yamaguchi, Takuma; Fukuda, Hisato; Furukawa, Ryo; Kawasaki, Hiroshi; Sturm, Peter.
Computer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers. PART 4. ed. 2011. p. 127-140 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6495 LNCS, No. PART 4).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Video deblurring and super-resolution technique for multiple moving objects
AU - Yamaguchi, Takuma
AU - Fukuda, Hisato
AU - Furukawa, Ryo
AU - Kawasaki, Hiroshi
AU - Sturm, Peter
PY - 2011/3/16
Y1 - 2011/3/16
N2 - Video camera is now commonly used and demand of capturing a single frame from video sequence is increasing. Since resolution of video camera is usually lower than digital camera and video data usually contains a many motion blur in the sequence, simple frame capture can produce only low quality image; image restoration technique is inevitably required. In this paper, we propose a method to restore a sharp and high-resolution image from a video sequence by motion deblur for each frame followed by super-resolution technique. Since the frame-rate of the video camera is high and variance of feature appearance in successive frames and motion of feature points are usually small, we can still estimate scene geometries from video data with blur. Therefore, by using such geometric information, we first apply motion deblur for each frame, and then, super-resolve the images from the deblurred image set. For better result, we also propose an adaptive super-resolution technique considering different defocus blur effects dependent on depth. Experimental results are shown to prove the strength of our method.
AB - Video camera is now commonly used and demand of capturing a single frame from video sequence is increasing. Since resolution of video camera is usually lower than digital camera and video data usually contains a many motion blur in the sequence, simple frame capture can produce only low quality image; image restoration technique is inevitably required. In this paper, we propose a method to restore a sharp and high-resolution image from a video sequence by motion deblur for each frame followed by super-resolution technique. Since the frame-rate of the video camera is high and variance of feature appearance in successive frames and motion of feature points are usually small, we can still estimate scene geometries from video data with blur. Therefore, by using such geometric information, we first apply motion deblur for each frame, and then, super-resolve the images from the deblurred image set. For better result, we also propose an adaptive super-resolution technique considering different defocus blur effects dependent on depth. Experimental results are shown to prove the strength of our method.
UR - http://www.scopus.com/inward/record.url?scp=79952510995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79952510995&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-19282-1_11
DO - 10.1007/978-3-642-19282-1_11
M3 - Conference contribution
SN - 9783642192814
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 140
BT - Computer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers
ER -