TY - GEN
T1 - Multi-scale/multi-resolution Kronecker compressive imaging
AU - Canh, Thuong Nguyen
AU - Dinh, Khanh Quoc
AU - Jeon, Byeungwoo
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/9
Y1 - 2015/12/9
N2 - As a universal sampling procedure, compressive sensing (CS) considers that all samples of compressible signal are equally important. However, it is not true in in image/video signal since human visual system is more sensitive to low frequency components. Therefore, CS theory has been extended to hybrid and multi-scale CS to better capture the low-frequency samples. The computational complexity is another challenge in CS which can be solved by multi-resolution sensing matrix. In this paper, we propose a multi-scale/multi-resolution sensing matrix for Kronecker CS (KCS) based on separable wavelet transform and address measurement allocation problem with and without information of to-be-sensed image. The proposed methods not only perform better (3.72dB gain) but also low complexity and compatible with conventional reconstruction methods.
AB - As a universal sampling procedure, compressive sensing (CS) considers that all samples of compressible signal are equally important. However, it is not true in in image/video signal since human visual system is more sensitive to low frequency components. Therefore, CS theory has been extended to hybrid and multi-scale CS to better capture the low-frequency samples. The computational complexity is another challenge in CS which can be solved by multi-resolution sensing matrix. In this paper, we propose a multi-scale/multi-resolution sensing matrix for Kronecker CS (KCS) based on separable wavelet transform and address measurement allocation problem with and without information of to-be-sensed image. The proposed methods not only perform better (3.72dB gain) but also low complexity and compatible with conventional reconstruction methods.
KW - Kronecker compressive sensing
KW - measurement allocation
KW - multi-resolution
KW - multi-scale
UR - https://www.scopus.com/pages/publications/84956622050
U2 - 10.1109/ICIP.2015.7351293
DO - 10.1109/ICIP.2015.7351293
M3 - Conference contribution
AN - SCOPUS:84956622050
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2700
EP - 2704
BT - 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PB - IEEE Computer Society
T2 - IEEE International Conference on Image Processing, ICIP 2015
Y2 - 27 September 2015 through 30 September 2015
ER -