TY - GEN
T1 - Efficient image reconstruction using partial 2D fourier transform
AU - Deng, L.
AU - Yu, C. L.
AU - Chakrabarti, Chaitali
AU - Kim, J.
AU - Narayanan, V.
PY - 2008
Y1 - 2008
N2 - In this paper we present an efficient way of doing image reconstruction using the 2D Discrete Fourier transform (DFT). We exploit the fact that in the frequency domain, information is concentrated in certain regions. Consequently, it is sufficient to compute partial 2D Fourier transform where only m × m elements of an A × N image are nonzero. Compared with the traditional row-column (RC) decomposition algorithm, the proposed algorithm enables us to reconstruct images with significantly smaller computation complexity at the expense of mild degradation in quality. We also describe the implementation of the new reconstruction algorithm on a Xilinx Virtex-II Pro-100 FPGA. For 512 × 512 natural and aerial images, this implementation results in 68% reduction in the number of memory accesses and 76% reduction in the total computation time compared to the RC method.
AB - In this paper we present an efficient way of doing image reconstruction using the 2D Discrete Fourier transform (DFT). We exploit the fact that in the frequency domain, information is concentrated in certain regions. Consequently, it is sufficient to compute partial 2D Fourier transform where only m × m elements of an A × N image are nonzero. Compared with the traditional row-column (RC) decomposition algorithm, the proposed algorithm enables us to reconstruct images with significantly smaller computation complexity at the expense of mild degradation in quality. We also describe the implementation of the new reconstruction algorithm on a Xilinx Virtex-II Pro-100 FPGA. For 512 × 512 natural and aerial images, this implementation results in 68% reduction in the number of memory accesses and 76% reduction in the total computation time compared to the RC method.
KW - Discrete fourier transform
KW - FPGA
KW - Image reconstruction
KW - Row-column decomposition
KW - Two dimensional decomposition
UR - http://www.scopus.com/inward/record.url?scp=57849158252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57849158252&partnerID=8YFLogxK
U2 - 10.1109/SIPS.2008.4671736
DO - 10.1109/SIPS.2008.4671736
M3 - Conference contribution
AN - SCOPUS:57849158252
SN - 9781424429240
T3 - IEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
SP - 49
EP - 54
BT - 2008 IEEE Workshop on Signal Processing Systems, SiPS 2008, Proceedings
T2 - 2008 IEEE Workshop on Signal Processing Systems, SiPS 2008
Y2 - 8 October 2008 through 10 October 2008
ER -