TY - GEN
T1 - A METHOD FOR ADDING MOTION-BLUR ON ARBITRARY OBJECTS BY USING AUTO-SEGMENTATION AND COLOR COMPENSATION TECHNIQUES
AU - Mikamo, Michihiro
AU - Furukawa, Ryo
AU - Kawasaki, Hiroshi
N1 - Funding Information:
Acknowledgment This work was supported by JSPS/KAKENHI 20H00611, 18K19824, 18H04119 in Japan.
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - When dynamic objects are captured by a camera, motion blur inevitably occurs. Such a blur is sometimes considered as just a noise, however, it sometimes gives an important effect to add dynamism in the scene for photographs or videos. Unlike the similar effects, such as defocus blur, which is now easily controlled even by smartphones, motion blur is still uncontrollable and makes undesired effects on photographs. In this paper, an unified framework to add motion blur on per-object basis is proposed. In the method, multiple frames are captured without motion blur and they are accumulated to create motion blur on target objects. To capture images without motion blur, shutter speed must be short, however, it makes captured images dark, and thus, a sensor gain should be increased to compensate it. Since a sensor gain causes a severe noise on image, we propose a color compensation algorithm based on non-linear filtering technique for solution. Another contribution is that our technique can be used to make HDR images for fast moving objects by using multi-exposure images. In the experiments, effectiveness of the method is confirmed by ablation study using several data sets.
AB - When dynamic objects are captured by a camera, motion blur inevitably occurs. Such a blur is sometimes considered as just a noise, however, it sometimes gives an important effect to add dynamism in the scene for photographs or videos. Unlike the similar effects, such as defocus blur, which is now easily controlled even by smartphones, motion blur is still uncontrollable and makes undesired effects on photographs. In this paper, an unified framework to add motion blur on per-object basis is proposed. In the method, multiple frames are captured without motion blur and they are accumulated to create motion blur on target objects. To capture images without motion blur, shutter speed must be short, however, it makes captured images dark, and thus, a sensor gain should be increased to compensate it. Since a sensor gain causes a severe noise on image, we propose a color compensation algorithm based on non-linear filtering technique for solution. Another contribution is that our technique can be used to make HDR images for fast moving objects by using multi-exposure images. In the experiments, effectiveness of the method is confirmed by ablation study using several data sets.
UR - http://www.scopus.com/inward/record.url?scp=85125571851&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85125571851&partnerID=8YFLogxK
U2 - 10.1109/ICIP42928.2021.9506443
DO - 10.1109/ICIP42928.2021.9506443
M3 - Conference contribution
AN - SCOPUS:85125571851
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1854
EP - 1858
BT - 2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
PB - IEEE Computer Society
T2 - 2021 IEEE International Conference on Image Processing, ICIP 2021
Y2 - 19 September 2021 through 22 September 2021
ER -