|
|
|
|
LEADER |
01000caa a22002652c 4500 |
001 |
NLM331549557 |
003 |
DE-627 |
005 |
20250302133844.0 |
007 |
cr uuu---uuuuu |
008 |
231225s2022 xx |||||o 00| ||eng c |
024 |
7 |
|
|a 10.1109/TPAMI.2021.3117962
|2 doi
|
028 |
5 |
2 |
|a pubmed25n1104.xml
|
035 |
|
|
|a (DE-627)NLM331549557
|
035 |
|
|
|a (NLM)34613909
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Jiang, Deyang
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Ring and Radius Sampling Based Phasor Field Diffraction Algorithm for Non-Line-of-Sight Reconstruction
|
264 |
|
1 |
|c 2022
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
500 |
|
|
|a Date Revised 05.10.2022
|
500 |
|
|
|a published: Print-Electronic
|
500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
520 |
|
|
|a Non-Line-of-Sight (NLOS) imaging reconstructs occluded scenes based on indirect diffuse reflections. The computational complexity and memory consumption of existing NLOS reconstruction algorithms make them challenging to be implemented in real-time. This paper presents a fast and memory-efficient phasor field-diffraction-based NLOS reconstruction algorithm. In the proposed algorithm, the radial property of the Rayleigh Sommerfeld diffraction (RSD) kernels along with the linear property of Fourier transform are utilized to reconstruct the Fourier domain representations of RSD kernels using a set of kernel bases. Moreover, memory consumption is further reduced by sampling the kernel bases in a radius direction and constructing them during the run-time. According to the analysis, the memory efficiency can be improved by as much as 220×. Experimental results show that compared with the original RSD algorithm, the reconstruction time of the proposed algorithm is significantly reduced with little impact on the final imaging quality
|
650 |
|
4 |
|a Journal Article
|
700 |
1 |
|
|a Liu, Xiaochun
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Luo, Jianwen
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Liao, Zhengpeng
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Velten, Andreas
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Lou, Xin
|e verfasserin
|4 aut
|
773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 44(2022), 11 vom: 15. Nov., Seite 7841-7853
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnas
|
773 |
1 |
8 |
|g volume:44
|g year:2022
|g number:11
|g day:15
|g month:11
|g pages:7841-7853
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TPAMI.2021.3117962
|3 Volltext
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_NLM
|
912 |
|
|
|a GBV_ILN_350
|
951 |
|
|
|a AR
|
952 |
|
|
|d 44
|j 2022
|e 11
|b 15
|c 11
|h 7841-7853
|