Serkan ErgunMurat KurtAydin ÖztürkErgun, SerkanKurt, MuratOzturk, Aydn2025-10-062012978145031977510.1145/2448531.24485412-s2.0-84876217584https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876217584&doi=10.1145%2F2448531.2448541&partnerID=40&md5=e10158698078ef7c7ee084b1972e681ehttps://gcris.yasar.edu.tr/handle/123456789/10160https://doi.org/10.1145/2448531.2448541We present a new real-time importance sampling algorithm for environment maps. Our method is based on representing environment maps using kd-tree structures and generating samples with a single data lookup. An efficient algorithm has been developed for realtime image-based lighting applications. In this paper we compared our algorithm with Inversion method [Fishman 1996]. We show that our proposed algorithm provides compactness and speedup as compared to Inversion method. Based on a number of rendered images we have demonstrated that in a fixed time frame the proposed algorithm produces images with a lower noise than that of the Inversion method. We also demonstrate that our algorithm can successfully represent a wide range of material types. © 2013 ACM. © 2013 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessEnvironment Maps, Global Illumination, Gpu, Importance Sampling, Kd-tree, Monte Carlo Integration, Rendering, Environment Maps, Global Illumination, Gpu, Kd-tree, Monte Carlo Integration, Rendering, Computer Graphics, Forestry, Importance Sampling, Trees (mathematics), Algorithms, Maps, SamplingEnvironment maps, Global illumination, GPU, Kd-tree, Monte Carlo integration, Rendering, Computer graphics, Forestry, Importance sampling, Trees (mathematics), Algorithms, Maps, SamplingMonte Carlo IntegrationEnvironment MapsRenderingGlobal IlluminationImportance SamplingGPUKd-treeConference Object