000164056 001__ 164056
000164056 005__ 20251121161351.0
000164056 0247_ $$2doi$$a10.3390/s25206492
000164056 0248_ $$2sideral$$a146131
000164056 037__ $$aART-2025-146131
000164056 041__ $$aeng
000164056 100__ $$0(orcid)0000-0003-1683-4694$$aSerón, Francisco J.$$uUniversidad de Zaragoza
000164056 245__ $$aWorkflow Analysis for CGH Generation with Speckle Reduction and Occlusion Culling Using GPU Acceleration
000164056 260__ $$c2025
000164056 5060_ $$aAccess copy available to the general public$$fUnrestricted
000164056 5203_ $$aAlthough GPUs are widely used in Computer-Generated Holography (CGH), their specific application to concrete problems such as occlusion or speckle filtering through temporal multiplexing is not yet standardized and has not been fully explored. This work aims to optimize the software architecture by taking the GPU architecture into account in a novel way for these particular tasks. We present an optimized algorithm for CGH computation that provides a joint solution to the problems of speckle noise and occlusion. The workflow includes the generation and illumination of a 3D scene, the calculation of the CGH including color, occlusion, and temporal speckle-noise filtering, followed by scene reconstruction through both simulation and experimental methods. The research focuses on implementing a temporal multiplexing technique that simultaneously performs speckle denoising and occlusion culling for point clouds, evaluating two types of occlusion that differ in whether the occlusion effect dominates over the depth effect in a scene stored in a CGH, while leveraging the parallel processing capabilities of GPUs to achieve a more immersive and high-quality visual experience. To this end, the total computational cost associated with generating color and occlusion CGHs is evaluated, quantifying the relative contribution of each factor. The results indicate that, under strict occlusion conditions, temporal multiplexing filtering does not significantly impact the overall computational cost of CGH calculation.
000164056 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000164056 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000164056 700__ $$0(orcid)0000-0001-9688-2260$$aBlesa, Alfonso$$uUniversidad de Zaragoza
000164056 700__ $$aSanz, Diego$$uUniversidad de Zaragoza
000164056 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica
000164056 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000164056 773__ $$g25, 20 (2025), 6492 [21 pp.]$$pSensors$$tSensors$$x1424-8220
000164056 8564_ $$s14410142$$uhttps://zaguan.unizar.es/record/164056/files/texto_completo.pdf$$yVersión publicada
000164056 8564_ $$s2433789$$uhttps://zaguan.unizar.es/record/164056/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000164056 909CO $$ooai:zaguan.unizar.es:164056$$particulos$$pdriver
000164056 951__ $$a2025-11-21-14:25:37
000164056 980__ $$aARTICLE