Abstract
A wide-area image can be synthesized from an image sequence taken with a moving camera by using image mosaicing techniques. However, motion blur caused by the motion of the camera may significantly degrade the quality of the synthesized image. In this paper, we propose a new method for generating a deblurred mosaic from an image sequence that is degraded by motion blur under the condition that we do not have any information about the intrinsic and extrinsic parameters of the moving camera during input acquisition. In this method, we assume the objects in the scene can be classified into two regions in order to handle depth. In this paper, the displacement vectors of the features, which are computed using the KLT feature tracker on the consecutive frames, are classified into two regions. Here, the classified vectors provide a Point Spread Function (PSF) of the blurred image, and a homography between two consecutive frames for segmentation and mosaicing. Experimental results show that the Signal to Noise Ratio of the generated images can be significantly improved by our proposed method.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science |
| Editors | S. Singh, M. Singh, C. Apte, P. Perner |
| Pages | 598-607 |
| Number of pages | 10 |
| Volume | 3687 |
| Edition | PART II |
| Publication status | Published - 2005 |
| Event | Third International Conference on Advances in Patten Recognition, ICAPR 2005 - Bath, United Kingdom Duration: 2005 Aug 22 → 2005 Aug 25 |
Other
| Other | Third International Conference on Advances in Patten Recognition, ICAPR 2005 |
|---|---|
| Country | United Kingdom |
| City | Bath |
| Period | 05/8/22 → 05/8/25 |
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ASJC Scopus subject areas
- Computer Science (miscellaneous)
Cite this
Mosaicing and restoration from blurred image sequence taken with moving camera. / Onogi, Midori; Saito, Hideo.
Lecture Notes in Computer Science. ed. / S. Singh; M. Singh; C. Apte; P. Perner. Vol. 3687 PART II. ed. 2005. p. 598-607.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Mosaicing and restoration from blurred image sequence taken with moving camera
AU - Onogi, Midori
AU - Saito, Hideo
PY - 2005
Y1 - 2005
N2 - A wide-area image can be synthesized from an image sequence taken with a moving camera by using image mosaicing techniques. However, motion blur caused by the motion of the camera may significantly degrade the quality of the synthesized image. In this paper, we propose a new method for generating a deblurred mosaic from an image sequence that is degraded by motion blur under the condition that we do not have any information about the intrinsic and extrinsic parameters of the moving camera during input acquisition. In this method, we assume the objects in the scene can be classified into two regions in order to handle depth. In this paper, the displacement vectors of the features, which are computed using the KLT feature tracker on the consecutive frames, are classified into two regions. Here, the classified vectors provide a Point Spread Function (PSF) of the blurred image, and a homography between two consecutive frames for segmentation and mosaicing. Experimental results show that the Signal to Noise Ratio of the generated images can be significantly improved by our proposed method.
AB - A wide-area image can be synthesized from an image sequence taken with a moving camera by using image mosaicing techniques. However, motion blur caused by the motion of the camera may significantly degrade the quality of the synthesized image. In this paper, we propose a new method for generating a deblurred mosaic from an image sequence that is degraded by motion blur under the condition that we do not have any information about the intrinsic and extrinsic parameters of the moving camera during input acquisition. In this method, we assume the objects in the scene can be classified into two regions in order to handle depth. In this paper, the displacement vectors of the features, which are computed using the KLT feature tracker on the consecutive frames, are classified into two regions. Here, the classified vectors provide a Point Spread Function (PSF) of the blurred image, and a homography between two consecutive frames for segmentation and mosaicing. Experimental results show that the Signal to Noise Ratio of the generated images can be significantly improved by our proposed method.
UR - http://www.scopus.com/inward/record.url?scp=27244444427&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=27244444427&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:27244444427
VL - 3687
SP - 598
EP - 607
BT - Lecture Notes in Computer Science
A2 - Singh, S.
A2 - Singh, M.
A2 - Apte, C.
A2 - Perner, P.
ER -