Cite

Ahn, W. and Kim, J. -S. 2005. Flat-Region Detection and False Contour Removal in the Digital TV Display. 2005 IEEE International Conference on Multimedia and Expo, pp. 1338–1341.AhnW.KimJ. -S.2005Flat-Region Detection and False Contour Removal in the Digital TV Display2005 IEEE International Conference on Multimedia and Expopp.13381341Search in Google Scholar

Akyüz, A. O., Fleming, R., Riecke, B. E., Reinhard, E. and Bülthoff, H. H. 2007. Do HDR displays support LDR content? ACM Transactions on Graphics 26(3): 38.AkyüzA. O.FlemingR.RieckeB. E.ReinhardE.BülthoffH. H.2007Do HDR displays support LDR content?ACM Transactions on Graphics26(3):3810.1145/1275808.1276425Search in Google Scholar

Alpert, T. and Evain, J. 1997. Subjective quality evaluation – the SSCQE and DSCQE methodologies. EBU Technical Review 271: 12–20, available at: https://tech.ebu.ch/publications/trev_271-evain=0pt.AlpertT.EvainJ.1997Subjective quality evaluation – the SSCQE and DSCQE methodologiesEBU Technical Review2711220available at:https://tech.ebu.ch/publications/trev_271-evain=0pt.Search in Google Scholar

Artusi, A., Richter, T., Ebrahimi, T. and Mantiuk, R. K. 2017. High dynamic range imaging technology [Lecture notes]. IEEE Signal Processing Magazine 34(5): 165–172.ArtusiA.RichterT.EbrahimiT.MantiukR. K.2017High dynamic range imaging technology [Lecture notes]IEEE Signal Processing Magazine34(5):16517210.1109/MSP.2017.2716957Search in Google Scholar

Aydin, T. O., Mantiuk, R., Myszkowski, K. and Seidel, H. -P. 2008. Dynamic range independent image quality assessment. ACM Transactions on Graph 27(3): 69, available at: http://doi.acm.org/10.1145/1360612.1360668=0pt.AydinT. O.MantiukR.MyszkowskiK.SeidelH. -P.2008Dynamic range independent image quality assessmentACM Transactions on Graph27(3):69available at:http://doi.acm.org/10.1145/1360612.1360668=0pt10.1145/1399504.1360668Search in Google Scholar

Azimi, M., Boitard, R., Oztas, B., Ploumis, S., Tohidypour, H. R., Pourazad, M. T. and Nasiopoulos, P. 2015. Compression efficiency of HDR/LDR content. Quality of Multimedia Experience (QoMEX), 2015 Seventh International Workshop on IEEE, pp. 1–6.AzimiM.BoitardR.OztasB.PloumisS.TohidypourH. R.PourazadM. T.NasiopoulosP.2015Compression efficiency of HDR/LDR contentQuality of Multimedia Experience (QoMEX), 2015 Seventh International Workshop on IEEEpp.16Search in Google Scholar

Banterle, F., Ledda, P., Debattista, K. and Chalmers, A. 2006. Inverse tone mapping. Proceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, ser. GRAPHITE’06, ACM, New York, NY, pp. 349–356, available at: http://doi.acm.org/10.1145/1174429.1174489=0pt.BanterleF.LeddaP.DebattistaK.ChalmersA.2006Inverse tone mappingProceedings of the 4th International Conference on Computer Graphics and Interactive Techniques in Australasia and Southeast Asia, ser. GRAPHITE’06, ACM, New York, NYpp.349356available at:http://doi.acm.org/10.1145/1174429.1174489=0pt.10.1145/1174429.1174489Search in Google Scholar

Chandler, D. M. 2013. Seven challenges in image quality assessment: past, present, and future research. ISRN Signal Processing, Vol. 2013.ChandlerD. M.2013Seven challenges in image quality assessment: past, present, and future researchISRN Signal ProcessingVol.201310.1155/2013/905685Search in Google Scholar

Chua, T. W. and Shen, L. 2017. Contour detection from deep patch-level boundary prediction. 2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP), pp. 5–9.ChuaT. W.ShenL.2017Contour detection from deep patch-level boundary prediction2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP)pp.59Search in Google Scholar

Duan, L., Debattista, K., Lei, Z. and Chalmers, A. 2020. Subjective and objective evaluation of local dimming algorithms for HDR images. IEEE Access 8(51): 692–702.DuanL.DebattistaK.LeiZ.ChalmersA.2020Subjective and objective evaluation of local dimming algorithms for HDR imagesIEEE Access8(51):69270210.1109/ACCESS.2020.2980075Search in Google Scholar

Durand, F. and Dorsey, J. 2000. Interactive tone mapping. Eurographics, Springer, Vienna, pp. 219–230.DurandF.DorseyJ.2000Interactive tone mappingEurographics, SpringerViennapp.219230Search in Google Scholar

Eilertsen, G., Mantiuk, R. K. and Unger, J. 2015. Real-time noise-aware tone mapping. ACM Transactions on Graphics 34(6): 98:1–198:15, available at: http://doi.acm.org/10.1145/2816795.2818092=0pt.EilertsenG.MantiukR. K.UngerJ.2015Real-time noise-aware tone mappingACM Transactions on Graphics34(6):98:1–198:15available at:http://doi.acm.org/10.1145/2816795.2818092=0pt.10.1145/2816795.2818092Search in Google Scholar

El Mezeni, D. and Saranovac, L. 2018. Temporal adaptation control for local tone mapping operator. Journal of Electrical Engineering 69(4): 261–269.El MezeniD.SaranovacL.2018Temporal adaptation control for local tone mapping operatorJournal of Electrical Engineering69(4):26126910.2478/jee-2018-0037Search in Google Scholar

Ellahi, W., Vigier, T. and Le Callet, P. 2020. HMM-based framework to measure the visual fidelity of tone mapping operators. 2020 IEEE International Conference on Multimedia Expo Workshops (ICMEW), pp. 1–6.EllahiW.VigierT.Le CalletP.2020HMM-based framework to measure the visual fidelity of tone mapping operators2020 IEEE International Conference on Multimedia Expo Workshops (ICMEW)pp.16Search in Google Scholar

Fang, Y., Zhu, H., Ma, K., Wang, Z. and Li, S. 2020. Perceptual evaluation for multi-exposure image fusion of dynamic scenes. IEEE Transactions on Image Processing 29: 1127–1138.FangY.ZhuH.MaK.WangZ.LiS.2020Perceptual evaluation for multi-exposure image fusion of dynamic scenesIEEE Transactions on Image Processing291127113810.1109/TIP.2019.294067831535996Search in Google Scholar

Fang, Y., Yan, J., Du, R., Zuo, Y., Wen, W., Zeng, Y. and Li, L. 2021. Blind quality assessment for tone-mapped images by analysis of gradient and chromatic statistics. IEEE Transactions on Multimedia 23: 955–966.FangY.YanJ.DuR.ZuoY.WenW.ZengY.LiL.2021Blind quality assessment for tone-mapped images by analysis of gradient and chromatic statisticsIEEE Transactions on Multimedia2395596610.1109/TMM.2020.2991528Search in Google Scholar

Fattal, R., Lischinski, D. and Werman, M. 2002. Gradient domain high dynamic range compression. ACM Transactions on Graphics 21(3): 249–256.FattalR.LischinskiD.WermanM.2002Gradient domain high dynamic range compressionACM Transactions on Graphics21(3):24925610.1145/566570.566573Search in Google Scholar

Ferwerda, J. A., Pattanaik, S. N., Shirley, P. and Greenberg, D. P. 1996. A model of visual adaptation for realistic image synthesis. Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, ser. SIGGRAPH’96, ACM, New York, NY, pp. 249–258. available at: http://doi.acm.org/10.1145/237170.237262.FerwerdaJ. A.PattanaikS. N.ShirleyP.GreenbergD. P.1996A model of visual adaptation for realistic image synthesisProceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, ser. SIGGRAPH’96, ACM, New York, NYpp.249258available at:http://doi.acm.org/10.1145/237170.23726210.1145/237170.237262Search in Google Scholar

Goshtasby, A. A. 2005. Fusion of multi-exposure images. Image and Vision Computing 23(6): 611–618.GoshtasbyA. A.2005Fusion of multi-exposure imagesImage and Vision Computing23(6):61161810.1016/j.imavis.2005.02.004Search in Google Scholar

Gu, B., Li, W., Wong, J., Zhu, M. and Wang, M. 2012. Gradient field multi-exposure images fusion for high dynamic range image visualization. Journal of Visual Communication and Image Representation 23(4): 604–610.GuB.LiW.WongJ.ZhuM.WangM.2012Gradient field multi-exposure images fusion for high dynamic range image visualizationJournal of Visual Communication and Image Representation23(4):60461010.1016/j.jvcir.2012.02.009Search in Google Scholar

Guan, F., Jiang, G., Song, Y., Yu, M., Peng, Z. and Chen, F. 2018. No-reference HDR image quality assessment method based on tensor space. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp. 1218–1222.GuanF.JiangG.SongY.YuM.PengZ.ChenF.2018No-reference HDR image quality assessment method based on tensor space2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEEpp.12181222Search in Google Scholar

Gunawan, I. P. 2006. Reduced-reference impairment metrics for digitally compressed video. PhD dissertation, University of Essex.GunawanI. P.2006Reduced-reference impairment metrics for digitally compressed videoPhD dissertation, University of EssexSearch in Google Scholar

Hands, D. S. 1998. Mental processes in the evaluation of digitally-coded television pictures. PhD dissertation, University of Essex.HandsD. S.1998Mental processes in the evaluation of digitally-coded television picturesPhD dissertation, University of EssexSearch in Google Scholar

Huang, F., Zhou, D., Nie, R. and Yu, C. 2018a. A color multi-exposure image fusion approach using structural patch decomposition,” IEEE Access 6: 42877–42 885.HuangF.ZhouD.NieR.YuC.2018aA color multi-exposure image fusion approach using structural patch decomposition,”IEEE Access64287742 88510.1109/ACCESS.2018.2859355Search in Google Scholar

Huang, Q., Kim, H. Y., Tsai, W., Jeong, S. Y., Choi, J. S. and Kuo, C. J. 2018b. Understanding and removal of false contour in HEVC compressed images. IEEE Transactions on Circuits and Systems for Video Technology 28(2): 378–391.HuangQ.KimH. Y.TsaiW.JeongS. Y.ChoiJ. S.KuoC. J.2018bUnderstanding and removal of false contour in HEVC compressed imagesIEEE Transactions on Circuits and Systems for Video Technology28(2):37839110.1109/TCSVT.2016.2607258Search in Google Scholar

Jia, S., Zhang, Y., Agrafiotis, D. and Bull, D. 2017. Blind high dynamic range image quality assessment using deep learning. 2017 IEEE International Conference on Image Processing (ICIP), IEEE, pp. 765–769.JiaS.ZhangY.AgrafiotisD.BullD.2017Blind high dynamic range image quality assessment using deep learning2017 IEEE International Conference on Image Processing (ICIP), IEEEpp.765769Search in Google Scholar

Jiang, M., Shen, L., Zheng, L., Zhao, M. and Jiang, X. 2020. Tone-mapped image quality assessment for electronics displays by combining luminance partition and colorfulness index. IEEE Transactions on Consumer Electronics 66(2): 153–162.JiangM.ShenL.ZhengL.ZhaoM.JiangX.2020Tone-mapped image quality assessment for electronics displays by combining luminance partition and colorfulness indexIEEE Transactions on Consumer Electronics66(2):15316210.1109/TCE.2020.2985742Search in Google Scholar

Kim, D. and Kim, M. 2020. Learning-based low-complexity reverse tone mapping with linear mapping. IEEE Transactions on Circuits and Systems for Video Technology 30(2): 400–414.KimD.KimM.2020Learning-based low-complexity reverse tone mapping with linear mappingIEEE Transactions on Circuits and Systems for Video Technology30(2):40041410.1109/TCSVT.2019.2892438Search in Google Scholar

Kinoshita, Y., Shiota, S. and Kiya, H. 2017. “Fast inverse tone mapping with reinhard global operator”, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, New Orleans, LA, March 5–9.KinoshitaY.ShiotaS.KiyaH.2017“Fast inverse tone mapping with reinhard global operator”2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEENew Orleans, LAMarch 5–9Search in Google Scholar

Kinoshita, Y., Shiota, S., Kiya, H. and Yoshida, T. 2018. Multi-exposure image fusion based on exposure compensation. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp. 1388–1392.KinoshitaY.ShiotaS.KiyaH.YoshidaT.2018Multi-exposure image fusion based on exposure compensation2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEEpp.13881392Search in Google Scholar

Kovaleski, R. P. and Oliveira, M. M. 2009. High-quality brightness enhancement functions for real-time reverse tone mapping. The Visual Computer 25(5): 539–547, available at: https://doi.org/10.1007/s00371-009-0327-3=0pt.KovaleskiR. P.OliveiraM. M.2009High-quality brightness enhancement functions for real-time reverse tone mappingThe Visual Computer25(5):539547available at:https://doi.org/10.1007/s00371-009-0327-3=0pt10.1007/s00371-009-0327-3Search in Google Scholar

Krasula, L., Fliegel, K. and Le Callet, P. 2020. FFTMI: features fusion for natural tone-mapped images quality evaluation. IEEE Transactions on Multimedia 22(8): 2038–2047.KrasulaL.FliegelK.Le CalletP.2020FFTMI: features fusion for natural tone-mapped images quality evaluationIEEE Transactions on Multimedia22(8):2038204710.1109/TMM.2019.2952256Search in Google Scholar

Kundu, D., Ghadiyaram, D., Bovik, A. C. and Evans, B. L. 2017a. Large-scale crowdsourced study for tone-mapped HDR pictures. IEEE Transactions on Image Processing 26(10): 4725–4740.KunduD.GhadiyaramD.BovikA. C.EvansB. L.2017aLarge-scale crowdsourced study for tone-mapped HDR picturesIEEE Transactions on Image Processing26(10):4725474010.1109/TIP.2017.271394528613173Search in Google Scholar

Kundu, D., Ghadiyaram, D., Bovik, A. C. and Evans, B. L. 2017b. No-reference quality assessment of tone-mapped HDR pictures. IEEE Transactions on Image Processing 26(6): 2957–2971.KunduD.GhadiyaramD.BovikA. C.EvansB. L.2017bNo-reference quality assessment of tone-mapped HDR picturesIEEE Transactions on Image Processing26(6):2957297110.1109/TIP.2017.268594128333633Search in Google Scholar

Landis, H. 2002. Production-ready global illumination. Siggraph Course Notes 16: 87–101.LandisH.2002Production-ready global illuminationSiggraph Course Notes1687101Search in Google Scholar

Larson, G. W., Rushmeier, H. and Piatko, C. 1997. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Transactions on Visualization and Computer Graphics 3(4): 291–306.LarsonG. W.RushmeierH.PiatkoC.1997A visibility matching tone reproduction operator for high dynamic range scenesIEEE Transactions on Visualization and Computer Graphics3(4)29130610.2172/486125Search in Google Scholar

Li, S. and Kang, X. 2012. Fast multi-exposure image fusion with median filter and recursive filter. IEEE Transactions on Consumer Electronics 58(2): 626–632.LiS.KangX.2012Fast multi-exposure image fusion with median filter and recursive filterIEEE Transactions on Consumer Electronics58(2):62663210.1109/TCE.2012.6227469Search in Google Scholar

Li, Z. G., Zheng, J. H. and Rahardja, S. 2012. Detail-enhanced exposure fusion. IEEE Transactions on Image Processing 21(11): 4672–4676.LiZ. G.ZhengJ. H.RahardjaS.2012Detail-enhanced exposure fusionIEEE Transactions on Image Processing21(11):4672467610.1109/TIP.2012.220739622801512Search in Google Scholar

Lokmanwar, S. D. and Bhalchandra, A. S. 2019. Contour detection based on Gaussian filter. 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA), pp. 722–725.LokmanwarS. D.BhalchandraA. S.2019Contour detection based on Gaussian filter2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA)pp.722725Search in Google Scholar

Ma, K., Zeng, K. and Wang, Z. 2015. Perceptual quality assessment for multi-exposure image fusion. IEEE Transactions on Image Processing 24(11): 3345–3356.MaK.ZengK.WangZ.2015Perceptual quality assessment for multi-exposure image fusionIEEE Transactions on Image Processing24(11):3345335610.1109/TIP.2015.244292026068317Search in Google Scholar

Manno-Kovacs, A. 2019. Direction selective contour detection for salient objects. IEEE Transactions on Circuits and Systems for Video Technology 29(2): 375–389.Manno-KovacsA.2019Direction selective contour detection for salient objectsIEEE Transactions on Circuits and Systems for Video Technology29(2):37538910.1109/TCSVT.2018.2804438Search in Google Scholar

Mantiuk, R., Daly, S. J., Myszkowski, K. and Seidel, H. -P. 2005. Predicting visible differences in high dynamic range images: model and its calibration. Human Vision and Electronic Imaging X, vol. 5666, International Society for Optics and Photonics, pp. 204–215.MantiukR.DalyS. J.MyszkowskiK.SeidelH. -P.2005Predicting visible differences in high dynamic range images: model and its calibrationHuman Vision and Electronic Imaging X, vol. 5666, International Society for Optics and Photonicspp.204215Search in Google Scholar

Mantiuk, R., Myszkowski, K. and Seidel, H. -P. 2006. A perceptual framework for contrast processing of high dynamic range images. ACM Transactions on Applied Perception (TAP) 3(3): 286–308.MantiukR.MyszkowskiK.SeidelH. -P.2006A perceptual framework for contrast processing of high dynamic range imagesACM Transactions on Applied Perception (TAP)3(3):28630810.1145/1080402.1080418Search in Google Scholar

Mantiuk, R., Kim, K. J., Rempel, A. G. and Heidrich, W. 2011. HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditions. ACM Transactions on Graphics (TOG) 30(4): 40.MantiukR.KimK. J.RempelA. G.HeidrichW.2011HDR-VDP-2: a calibrated visual metric for visibility and quality predictions in all luminance conditionsACM Transactions on Graphics (TOG)30(4):4010.1145/1964921.1964935Search in Google Scholar

Mantiuk, R. K., Tomaszewska, A. and Mantiuk, R. 2012. Comparison of four subjective methods for image quality assessment. Computer Graphics Forum 31(8): 2478–2491, available at: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-8659.2012.03188.x=0pt.MantiukR. K.TomaszewskaA.MantiukR.2012Comparison of four subjective methods for image quality assessmentComputer Graphics Forum31(8):24782491available at:https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-8659.2012.03188.x=0pt.10.1111/j.1467-8659.2012.03188.xSearch in Google Scholar

Mantiuk, R. K., Myszkowski, K. and Seidel, H. -P. 2016. High dynamic range imaging. Wiley Encyclopedia of Electrical and Electronics Engineering, available at: https://www.cl.cam.ac.uk/rkm38/hdri_book.html=0pt.MantiukR. K.MyszkowskiK.SeidelH. -P.2016High dynamic range imagingWiley Encyclopedia of Electrical and Electronics Engineeringavailable at:https://www.cl.cam.ac.uk/rkm38/hdri_book.html=0pt10.1002/047134608X.W8265Search in Google Scholar

Mertens, T., Kautz, J. and Van Reeth, F. 2009. Exposure fusion: a simple and practical alternative to high dynamic range photography. Computer Graphics Forum 28(1): 161–171.MertensT.KautzJ.Van ReethF.2009Exposure fusion: a simple and practical alternative to high dynamic range photographyComputer Graphics Forum28(1):16117110.1111/j.1467-8659.2008.01171.xSearch in Google Scholar

Narwaria, M., Silva, M. P. D. and Callet, P. L. 2015. HDR-VQM: an objective quality measure for high dynamic range video. Signal Processing: Image Communication 35: 46–60, available at: https://www.sciencedirect.com/science/article/pii/S0923596515000703?via=0pt.NarwariaM.SilvaM. P. D.CalletP. L.2015HDR-VQM: an objective quality measure for high dynamic range videoSignal Processing: Image Communication354660available at:https://www.sciencedirect.com/science/article/pii/S0923596515000703?via=0pt10.1016/j.image.2015.04.009Search in Google Scholar

Nuutinen, M., Virtanen, T., Leisti, T., Mustonen, T., Radun, J. and Häkkinen, J. 2016. A new method for evaluating the subjective image quality of photographs: dynamic reference. Multimedia Tools and Applications 75(4): 2367–2391, available at: https://doi.org/10.1007/s11042-014-2410-7=0pt.NuutinenM.VirtanenT.LeistiT.MustonenT.RadunJ.HäkkinenJ.2016A new method for evaluating the subjective image quality of photographs: dynamic referenceMultimedia Tools and Applications75(4):23672391available at:https://doi.org/10.1007/s11042-014-2410-7=0pt10.1007/s11042-014-2410-7Search in Google Scholar

Opozda, S. and Sochan, A. 2014. The survey of subjective and objective methods for quality assessment of 2D and 3D images. Theoretical and Applied Informatics 26(1-2): 39–67.OpozdaS.SochanA.2014The survey of subjective and objective methods for quality assessment of 2D and 3D imagesTheoretical and Applied Informatics26(1-2):3967Search in Google Scholar

Patil, S. B. and Patil, S. R. 2017. Survey on approaches used for image quality assessment. 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), pp. 987–991.PatilS. B.PatilS. R.2017Survey on approaches used for image quality assessment2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)pp.987991Search in Google Scholar

Persson, M. 2014. “Subjective image quality evaluation using the softcopy quality ruler method,” student Paper.PerssonM.2014“Subjective image quality evaluation using the softcopy quality ruler method,”student PaperSearch in Google Scholar

Qiu, G., Guan, J., Duan, J. and Chen, M. 2006. Tone mapping for HDR image using optimization a new closed form solution. 18th International Conference on Pattern Recognition (ICPR’06), vol. 1, pp. 996–999.QiuG.GuanJ.DuanJ.ChenM.2006Tone mapping for HDR image using optimization a new closed form solution18th International Conference on Pattern Recognition (ICPR’06), vol. 1pp.996999Search in Google Scholar

Rahayu, F. N. 2011. Quality of experience for digital cinema presentation. PhD Thesis, Norwegian University of Science and Technology, available at: https://brage.bibsys.no/xmlui/handle/11250/2370392 http://hdl.handle.net/11250/2370392=0pt.RahayuF. N.2011Quality of experience for digital cinema presentationPhD Thesis, Norwegian University of Science and Technologyavailable at:https://brage.bibsys.no/xmlui/handle/11250/2370392http://hdl.handle.net/11250/2370392=0pt.Search in Google Scholar

Rana, A., Valenzise, G. and Dufaux, F. 2019. Learning-based tone mapping operator for efficient image matching. IEEE Transactions on Multimedia 21(1): 256–268.RanaA.ValenziseG.DufauxF.2019Learning-based tone mapping operator for efficient image matchingIEEE Transactions on Multimedia21(1):25626810.1109/TMM.2018.2839885Search in Google Scholar

Ravuri, C. S., Sureddi, R., Reddy Dendi, S. V., Raman, S. and Channappayya, S. S. 2019. Deep no-reference tone mapped image quality assessment. 2019 53rd Asilomar Conference on Signals, Systems, and Computers, pp. 1906–1910.RavuriC. S.SureddiR.Reddy DendiS. V.RamanS.ChannappayyaS. S.2019Deep no-reference tone mapped image quality assessment2019 53rd Asilomar Conference on Signals, Systems, and Computerspp.19061910Search in Google Scholar

Redi, J., Liu, H., Alers, H., Zunino, R. and Heynderickx, I. 2010. “Comparing subjective image quality measurement methods for the creation of public databases”, In Farnand, S. P. and Gaykema, F. (Eds), Image Quality and System Performance VII, vol. 7529 International Society for Optics and Photonics, SPIE, pp. 19–29, available at: https://doi.org/10.1117/12.839195=0pt.RediJ.LiuH.AlersH.ZuninoR.HeynderickxI.2010“Comparing subjective image quality measurement methods for the creation of public databases”InFarnandS. P.GaykemaF.(Eds)Image Quality and System Performance VII, vol. 7529International Society for Optics and Photonics, SPIEpp.1929available at:https://doi.org/10.1117/12.839195=0pt10.1117/12.839195Search in Google Scholar

Reinhard, E., Stark, M., Shirley, P. and Ferwerda, J. 2002. Photographic tone reproduction for digital images. ACM Transactions on Graphics 21(3): 267–276, available at: http://doi.acm.org/10.1145/566654.566575=0pt.ReinhardE.StarkM.ShirleyP.FerwerdaJ.2002Photographic tone reproduction for digital imagesACM Transactions on Graphics21(3):267276available at:http://doi.acm.org/10.1145/566654.566575=0pt.10.1145/566570.566575Search in Google Scholar

Reinhard, E., Heidrich, W., Debevec, P., Pattanaik, S., Ward, G. and Myszkowski, K. 2010. High Dynamic Range Imaging: Acquisition, Display, and Image-based Lighting Morgan Kaufmann, Amsterdam.ReinhardE.HeidrichW.DebevecP.PattanaikS.WardG.MyszkowskiK.2010High Dynamic Range Imaging: Acquisition, Display, and Image-based LightingMorgan KaufmannAmsterdamSearch in Google Scholar

Rovid, A., Varkonyi-Koczy, A. R., Hashimoto, T., Balogh, S. and Shimodaira, Y. 2007. Gradient based synthesized multiple exposure time HDR image. 2007 IEEE Instrumentation Measurement Technology Conference IMTC 2007, pp. 1–6.RovidA.Varkonyi-KoczyA. R.HashimotoT.BaloghS.ShimodairaY.2007Gradient based synthesized multiple exposure time HDR image2007 IEEE Instrumentation Measurement Technology Conference IMTC 2007pp.16Search in Google Scholar

RRNR-TV Group 2004. Test plan draft version 1.7 h, =2 plus 4 3 minus 4, available at: http://www.vqeg.org=0pt.RRNR-TV Group2004Test plan draft version 1.7 h, =2 plus 4 3 minus 4available at:http://www.vqeg.org=0ptSearch in Google Scholar

Sheikh, H. R., Sabir, M. F. and Bovik, A. C. 2006. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Transactions on Image Processing 15(11): 3440–3451.SheikhH. R.SabirM. F.BovikA. C.2006A statistical evaluation of recent full reference image quality assessment algorithmsIEEE Transactions on Image Processing15(11):3440345110.1109/TIP.2006.88195917076403Search in Google Scholar

Shen, R., Cheng, I. and Basu, A. 2013. QoE-based multi-exposure fusion in hierarchical multivariate Gaussian CRF. IEEE Transactions on Image Processing 22(6): 2469–2478.ShenR.ChengI.BasuA.2013QoE-based multi-exposure fusion in hierarchical multivariate Gaussian CRFIEEE Transactions on Image Processing22(6):2469247810.1109/TIP.2012.223634623288338Search in Google Scholar

Song, M., Tao, D., Chen, C., Bu, J., Luo, J. and Zhang, C. 2012. Probabilistic exposure fusion. IEEE Transactions on Image Processing 21(1): 341–357.SongM.TaoD.ChenC.BuJ.LuoJ.ZhangC.2012Probabilistic exposure fusionIEEE Transactions on Image Processing21(1):34135710.1109/TIP.2011.215751421609883Search in Google Scholar

The University of Texas at Austin 2006. LIVE Public-Domain Subjective Image Quality Database, available at: http://live.ece.utexas.edu/research/quality/subjective.htm=0pt.The University of Texas at Austin2006LIVE Public-Domain Subjective Image Quality Databaseavailable at:http://live.ece.utexas.edu/research/quality/subjective.htm=0ptSearch in Google Scholar

van Dijk, A. M., Martens, J. -B. and Watson, A. B. 1995. “Quality asessment of coded images using numerical category scaling”, In Ohta, N., Lemke, H. U. and Lehureau, J. C. (Eds), Advanced Image and Video Communications and Storage Technologies, Vol. 2451 International Society for Optics and Photonics SPIE, Amsterdam, pp. 90–101, available at: https://doi.org/10.1117/12.201231=0ptvan DijkA. M.MartensJ. -B.WatsonA. B.1995“Quality asessment of coded images using numerical category scaling”InOhtaN.LemkeH. U.LehureauJ. C.(Eds)Advanced Image and Video Communications and Storage Technologies, Vol. 2451International Society for Optics and Photonics SPIEAmsterdampp.90101available at:https://doi.org/10.1117/12.201231=0pt10.1117/12.201231Search in Google Scholar

Varkonyi-Koczy, A. R., Rovid, A. and Hashimoto, T. 2008. Gradient-based synthesized multiple exposure time color HDR image. IEEE Transactions on Instrumentation and Measurement 57(8): 1779–1785.Varkonyi-KoczyA. R.RovidA.HashimotoT.2008Gradient-based synthesized multiple exposure time color HDR imageIEEE Transactions on Instrumentation and Measurement57(8):1779178510.1109/TIM.2008.925715Search in Google Scholar

Video Quality Experts Group 2002. =2 plus 4 3 minus 4, available at: http://www.vqeg.org=0pt.Video Quality Experts Group2002=2 plus 4 3 minus 4available at:http://www.vqeg.org=0ptSearch in Google Scholar

VQEG 2000. Final report from the Video Quality Expert Group on the validation of objective models of video quality assessment – Phase I, VQEG, March, available at: http://www.vqeg.org=0pt.VQEG2000Final report from the Video Quality Expert Group on the validation of objective models of video quality assessment – Phase I, VQEG, Marchavailable at:http://www.vqeg.org=0pt.Search in Google Scholar

Wang, Z., Simoncelli, E. P. and Bovik, A. C. 2003. Multiscale structural similarity for image quality assessment. The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, vol. 2, IEEE, pp. 1398–1402.WangZ.SimoncelliE. P.BovikA. C.2003Multiscale structural similarity for image quality assessmentThe Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, vol. 2, IEEEpp.13981402Search in Google Scholar

Wang, X., Jiang, Q., Shao, F., Gu, K., Zhai, G. and Yang, X. 2021. Exploiting local degradation characteristics and global statistical properties for blind quality assessment of tone-mapped HDR images. IEEE Transactions on Multimedia 23: 692–705.WangX.JiangQ.ShaoF.GuK.ZhaiG.YangX.2021Exploiting local degradation characteristics and global statistical properties for blind quality assessment of tone-mapped HDR imagesIEEE Transactions on Multimedia2369270510.1109/TMM.2020.2986583Search in Google Scholar

Winkler, S. 2005. Digital Video Quality: Vision Models and Metrics John Wiley & Sons, Chicester.WinklerS.2005Digital Video Quality: Vision Models and MetricsJohn Wiley & SonsChicester10.1002/9780470024065Search in Google Scholar

Yeganeh, H. and Wang, Z. 2013. Objective quality assessment of tone-mapped images. IEEE Transactions on Image Processing 22(2): 657–667.YeganehH.WangZ.2013Objective quality assessment of tone-mapped imagesIEEE Transactions on Image Processing22(2):65766710.1109/TIP.2012.222172523047872Search in Google Scholar

Yue, G., Yan, W. and Zhou, T. 2020. Reference less quality evaluation of tone-mapped HDR and multiexposure fused images. IEEE Transactions on Industrial Informatics 16(3): 1764–1775.YueG.YanW.ZhouT.2020Reference less quality evaluation of tone-mapped HDR and multiexposure fused imagesIEEE Transactions on Industrial Informatics16(3):1764177510.1109/TII.2019.2927527Search in Google Scholar

Yun, S. -H., Kim, T. -C. and Kim, J. H. 2012. Single exposure-based image fusion using multi-transformation. Consumer Electronics (GCCE), 2012 IEEE 1st Global Conference on IEEE, pp. 142–143.YunS. -H.KimT. -C.KimJ. H.2012Single exposure-based image fusion using multi-transformationConsumer Electronics (GCCE), 2012 IEEE 1st Global Conference on IEEEpp.142143Search in Google Scholar

Zeng, K., Ma, K., Hassen, R. and Wang, Z. 2014. Perceptual evaluation of multi-exposure image fusion algorithms. Quality of Multimedia Experience (QoMEX), 2014 Sixth International Workshop on. IEEE, pp. 7–12.ZengK.MaK.HassenR.WangZ.2014Perceptual evaluation of multi-exposure image fusion algorithmsQuality of Multimedia Experience (QoMEX), 2014 Sixth International Workshop on. IEEEpp.712Search in Google Scholar

Zhang, W. and Cham, W. -K. 2012. Gradient-directed multiexposure composition. IEEE Transactions on Image Processing 21(4): 2318–2323.ZhangW.ChamW. -K.2012Gradient-directed multiexposure compositionIEEE Transactions on Image Processing21(4):2318232310.1109/TIP.2011.217007921965210Search in Google Scholar

Zhu, W., Zhai, G., Hu, M., Liu, J. and Yang, X. 2018a. Arrow’s impossibility theorem inspired subjective image quality assessment approach. Signal Processing 145: 193–201, available at: http://www.sciencedirect.com/science/article/pii/S0165168417304164=0pt.ZhuW.ZhaiG.HuM.LiuJ.YangX.2018aArrow’s impossibility theorem inspired subjective image quality assessment approachSignal Processing145193201available at:http://www.sciencedirect.com/science/article/pii/S0165168417304164=0pt10.1016/j.sigpro.2017.12.001Search in Google Scholar

Zhu, W., Zhai, G., Hu, M., Liu, J. and Yang, X. 2018b. Arrow’s impossibility theorem inspired subjective image quality assessment approach. Signal Processing 145: 193–201.ZhuW.ZhaiG.HuM.LiuJ.YangX.2018bArrow’s impossibility theorem inspired subjective image quality assessment approachSignal Processing14519320110.1016/j.sigpro.2017.12.001Search in Google Scholar

eISSN:
1178-5608
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Engineering, Introductions and Overviews, other