000168526 001__ 168526
000168526 005__ 20260209162330.0
000168526 0247_ $$2doi$$a10.1117/12.3069294
000168526 0248_ $$2sideral$$a147450
000168526 037__ $$aART-2025-147450
000168526 041__ $$aeng
000168526 100__ $$aChristnacher, F.
000168526 245__ $$aInfluence of some acquisition parameters in non-line-of-sight imaging
000168526 260__ $$c2025
000168526 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168526 5203_ $$aOver the past few years, Non-Line-of-Sight (NLOS) scene reconstruction algorithms have made significant progress, transforming our ability to reconstruct environments and scenes that are hidden from the direct view. These algorithms employ sophisticated techniques such as f-k migration, back-propagation, or phasor-field models to reconstruct the scene and reveal hidden objects. However, a major challenge persists: the time required to acquire the vast amounts of data needed to generate a high-quality, high-resolution scene reconstruction. High-resolution scene reconstructions necessitate extensive data collection, often involving measurements of multi-scattered light, leading to substantial data volumes. This results in prolonged acquisition times and considerable computational costs. Therefore, a pressing issue is how to reduce acquisition time without sacrificing the accuracy and resolution of the final reconstruction. To tackle this challenge, we have systematically analyzed the impact of each of these acquisition parameters to understand their influence on both acquisition time and data-transient quality. Our goal is to identify the most significant parameters and adjust them to achieve the desired trade-off between speed and accuracy. One of the most pressing issues is how to reduce the acquisition time without compromising the accuracy and resolution of the final reconstruction. To get closer to real-time processing, it is essential to carefully consider the parameters involved in the acquisition phase. Key parameters including the sensor pixel calibration, the exposure time and number of images per frame, the camera field-of-view (FOV) and focus adjustment, all play a critical role in both the quality of the reconstruction and the time required to acquire the necessary data. Optimizing these acquisition parameters is key to improving the efficiency of the scene reconstruction process.
000168526 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000168526 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000168526 700__ $$aLaurenzis, M.
000168526 700__ $$aSchertzer, S.
000168526 700__ $$aSpaett, Alexander
000168526 700__ $$0(orcid)0000-0002-0601-4820$$aRedo-Sanchez, A.$$uUniversidad de Zaragoza
000168526 700__ $$0(orcid)0000-0002-7503-7022$$aGutierrez, D.$$uUniversidad de Zaragoza
000168526 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000168526 773__ $$g13678 (2025), 13 [12 pp.]$$tProceedings of SPIE - The International Society for Optical Engineering$$x1996-756X
000168526 8564_ $$s1534275$$uhttps://zaguan.unizar.es/record/168526/files/texto_completo.pdf$$yPostprint
000168526 8564_ $$s2384325$$uhttps://zaguan.unizar.es/record/168526/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000168526 909CO $$ooai:zaguan.unizar.es:168526$$particulos$$pdriver
000168526 951__ $$a2026-02-09-14:42:45
000168526 980__ $$aARTICLE