DocumentCode :
2598806
Title :
Regularized blur-assisted displacement field estimation
Author :
Tull, Damon L. ; Katsaggelos, Aggelos K.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
Volume :
3
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
85
Abstract :
Due to the finite acquisition time of practical cameras, objects can move during image acquisition, therefore introducing motion blur degradations. Traditionally, these degradations are treated as undesirable artifacts that should be removed before further processing. We consider the use of motion blur as an indication of scene motion. We present two robust regularized motion estimation algorithms that consider the use of (motion) blur in their formulation. The first algorithm uses motion blur as prior knowledge for the estimation of the motion field. The second algorithm considers the joint estimation of the motion and motion blur. Each approach results in a motion blur point spread field, a motion field and a restored image in an approach that is different from previous work. Preliminary results are presented
Keywords :
image restoration; image sequences; motion estimation; optical transfer function; blur-assisted displacement field estimation; image acquisition; image processing; image sequences; joint estimation; motion blur degradations; motion blur point spread field; motion prior; object motion; point spread function; regularized motion estimation algorithms; restored image; scene motion; Cameras; Degradation; Image restoration; Image sequences; Layout; Motion estimation; Photoreceptors; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560375
Filename :
560375
Link To Document :
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