TY - GEN
T1 - Multiframe blind deconvolution of passive millimeter wave images using variational dirichlet blur kernel estimation
AU - Mateos, Javier
AU - Lopez, Antonio
AU - Vega, Miguel
AU - Molina, Rafael
AU - Katsaggelos, Aggelos K.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/3
Y1 - 2016/8/3
N2 - Passive Millimeter Wave Images currently used to detect hidden threats suffer from low resolution, blur, and a very low signal-to-noise-ratio. These shortcomings render threat detection, both visual and automatic, very challenging. Furthermore, due to the presence of very severe noise, most of the blind image restoration methods fail to recover the system blurring kernel from a single image. In this paper we propose a robust Bayesian multiframe blind image deconvolution method that approximates the posterior distribution of the blur by a Dirichlet distribution. We show that this approach naturally incorporates the non-negativity and normalization constraints for the blur and cope well with the image noise. The performance of the proposed method is tested on both synthetic and real images.
AB - Passive Millimeter Wave Images currently used to detect hidden threats suffer from low resolution, blur, and a very low signal-to-noise-ratio. These shortcomings render threat detection, both visual and automatic, very challenging. Furthermore, due to the presence of very severe noise, most of the blind image restoration methods fail to recover the system blurring kernel from a single image. In this paper we propose a robust Bayesian multiframe blind image deconvolution method that approximates the posterior distribution of the blur by a Dirichlet distribution. We show that this approach naturally incorporates the non-negativity and normalization constraints for the blur and cope well with the image noise. The performance of the proposed method is tested on both synthetic and real images.
KW - Blind image deconvolution
KW - Passive millimeter wave imaging
KW - Variational Dirichlet
UR - http://www.scopus.com/inward/record.url?scp=85006711820&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006711820&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2016.7532845
DO - 10.1109/ICIP.2016.7532845
M3 - Conference contribution
AN - SCOPUS:85006711820
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2678
EP - 2682
BT - 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PB - IEEE Computer Society
T2 - 23rd IEEE International Conference on Image Processing, ICIP 2016
Y2 - 25 September 2016 through 28 September 2016
ER -