{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T18:21:38Z","timestamp":1773512498910,"version":"3.50.1"},"reference-count":40,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2020,3,1]]},"DOI":"10.1587\/transinf.2019edp7219","type":"journal-article","created":{"date-parts":[[2020,2,29]],"date-time":"2020-02-29T22:10:54Z","timestamp":1583014254000},"page":"660-673","source":"Crossref","is-referenced-by-count":8,"title":["Simultaneous Estimation of Object Region and Depth in Participating Media Using a ToF Camera"],"prefix":"10.1587","volume":"E103.D","author":[{"given":"Yuki","family":"FUJIMURA","sequence":"first","affiliation":[{"name":"Graduate School of Informatics, Kyoto University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Motoharu","family":"SONOGASHIRA","sequence":"additional","affiliation":[{"name":"Academic Center for Computing and Media Studies, Kyoto University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaaki","family":"IIYAMA","sequence":"additional","affiliation":[{"name":"Academic Center for Computing and Media Studies, Kyoto University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] T. Treibitz and Y.Y. Schechner, \u201cActive polarization descattering,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.31, no.3, pp.385-399, 2009. 10.1109\/tpami.2008.85","DOI":"10.1109\/TPAMI.2008.85"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] C. Tsiotsios, M.E. Angelopoulou, T. Kim, and A.J. Davison, \u201cBackscatter compensated photometric stereo with 3 sources,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2259-2266, 2014. 10.1109\/cvpr.2014.289","DOI":"10.1109\/CVPR.2014.289"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] P. Holland and R.E. Welsch, \u201cRobust regression using iteratively reweighted least-squares,\u201d Communications in Statistics \u00e2\u0102\u015e Theory and Method, vol.6, no.9, pp.813-827, 1977. 10.1080\/03610927708827533","DOI":"10.1080\/03610927708827533"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] J. Fox and S. Weisberg, \u201cRobust regression in R: An appendix to an R companion to applied regression,\u201d SAGE Publishing, 2002.","DOI":"10.32614\/CRAN.package.car"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] R. Chartrand and W. Yin, \u201cIteratively reweighted algorithms for compressive sensing,\u201d The IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.3869-3872, 2008. 10.1109\/icassp.2008.4518498","DOI":"10.1109\/ICASSP.2008.4518498"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] D. Wipf and S. Nagarajan, \u201cIterative reweighted l1 and l2 methods for finding sparse solutions,\u201d IEEE J. Sel. Topics Signal Process., vol.3, no.2, pp.317-329, 2010. 10.1109\/jstsp.2010.2042413","DOI":"10.1109\/JSTSP.2010.2042413"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] K. He, J. Sun, and X. Tang, \u201cSingle image haze removal using dark channel prior,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.33, no.12, pp.2341-2353, 2011. 10.1109\/tpami.2010.168","DOI":"10.1109\/TPAMI.2010.168"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] K. Nishino, L. Kratz, and S. Lombardi, \u201cBayesian defogging,\u201d International Journal of Computer Vision, vol.98, no.3, pp.263-278, 2012. 10.1007\/s11263-011-0508-1","DOI":"10.1007\/s11263-011-0508-1"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] R. Fattal, \u201cDehazing using color-lines,\u201d ACM Transactions on Graphics (TOG), vol.34, no.1, 2014. 10.1145\/2651362","DOI":"10.1145\/2651362"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] D. Berman, T. Treibitz, and S. Avidan, \u201cNon-local image dehazing,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1674-1682, 2016. 10.1109\/cvpr.2016.185","DOI":"10.1109\/CVPR.2016.185"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] B. Cai, X. Xu, K. Jia, C. Qing, and D. Tao, \u201cDehazenet: An end-to-end system for single image haze removal,\u201d IEEE Trans. Image Process., vol.25, no.11, pp.5187-5198, 2016. 10.1109\/tip.2016.2598681","DOI":"10.1109\/TIP.2016.2598681"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] W. Ren, S. Liu, H. Zhang, J. Pan, X. Cao, and M. Yang, \u201cSingle image dehazing via multi-scale convolutional neural networks,\u201d European Conference on Computer Vision (ECCV), pp.154-169, 2016. 10.1007\/978-3-319-46475-6_10","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] B. Li, X. Peng, Z. Wang, J. Xu, and D. Feng, \u201cAod-net: All-in-one dehazing network,\u201d The IEEE International Conference on Computer Vision (ICCV), pp.4770-4778, 2017. 10.1109\/iccv.2017.511","DOI":"10.1109\/ICCV.2017.511"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] H. Zhang and V.M. Patel, \u201cDensely connected pyramid dehazing network,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3194-3203, 2018. 10.1109\/cvpr.2018.00337","DOI":"10.1109\/CVPR.2018.00337"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] D. Yang and J. Sun, \u201cProximal dehaze-net: A prior learning-based deep network for single image dehazing,\u201d The European Conference on Computer Vision (ECCV), pp.702-717, 2018.","DOI":"10.1007\/978-3-030-01234-2_43"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] R.T. Tan, \u201cVisibility in bad weather from a single image,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-8, 2008. 10.1109\/cvpr.2008.4587643","DOI":"10.1109\/CVPR.2008.4587643"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] Z. Li, P. Tan, R.T. Tang, D. Zou, S.Z. Zhou, and L. Cheong, \u201cSimultaneous video defogging and stereo reconstruction,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.4988-4997, 2015. 10.1109\/cvpr.2015.7299133","DOI":"10.1109\/CVPR.2015.7299133"},{"key":"18","unstructured":"[18] Z. Murez, T. Treibitz, R. Ramamoorthi, and D.J. Kriegman, \u201cPhotometric stereo in a scattering medium,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.39, no.9, pp.1880-1891, 2017."},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] Y. Fujimura, M. Iiyama, A. Hashimoto, and M. Minoh, \u201cPhotometric stereo in participating media considering shape-dependent forward scatter,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.7445-7453, 2018. 10.1109\/cvpr.2018.00777","DOI":"10.1109\/CVPR.2018.00777"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] S.G. Narasimhan, S.K. Nayar, B. Sun, and S.J. Koppal, \u201cStructured light in scattering media,\u201d Proc. Tenth IEEE International Conference on Computer Vision, vol.I, pp.420-427, 2005. 10.1109\/iccv.2005.232","DOI":"10.1109\/ICCV.2005.232"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] J. Gu, S.K. Nayar, P.N. Belhumeur, and R. Ramamoorthi, \u201cCompressive structured light for recovering inhomogeneous participating media,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.35, no.3, pp.555-567, 2013.","DOI":"10.1109\/TPAMI.2012.130"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] J. Tian, Z. Murez, T. Cui, Z. Zhang, D. Kriegman, and R.Ramamoorthi, \u201cDepth and image restoration from light field in a scattering medium,\u201d Proc. IEEE International Conference on Computer Vision, pp.2401-2410, 2017. 10.1109\/iccv.2017.263","DOI":"10.1109\/ICCV.2017.263"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] Y. Asano, Y. Zheng, K. Nishino, and I. Sato, \u201cShape from water: Bispectral light absorption for depth recovery,\u201d European Conference on Computer Vision, pp.635-649, 2016. 10.1007\/978-3-319-46466-4_38","DOI":"10.1007\/978-3-319-46466-4_38"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[24] S. Fuchs, \u201cMultipath interference compensation in time-of-flight camera images,\u201d 2010 20th International Conference on Pattern Recognition, pp.3583-3586, 2010. 10.1109\/icpr.2010.874","DOI":"10.1109\/ICPR.2010.874"},{"key":"25","doi-asserted-by":"crossref","unstructured":"[25] D. Freedman, Y. Smolin, E. Krupka, I. Leichter, and M. Schmidt, \u201cSra: Fast removal of general multipath for tof sensors,\u201d European Conference on Computer Vision (ECCV), pp.234-249, 2014. 10.1007\/978-3-319-10590-1_16","DOI":"10.1007\/978-3-319-10590-1_16"},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] N. Naik, A. Kasambi, C. Rhemann, S. Izadi, R. Rasker, and S.B. Kang, \u201cA light transport model for mitigating multipath interference in time-of-flight sensors,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.73-81, 2015. 10.1109\/cvpr.2015.7298602","DOI":"10.1109\/CVPR.2015.7298602"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] A. Kadambi, J. Schiel, and R. Rasker, \u201cMacroscopic interferometry: Rethinking depth estimation with frequency-domain time-of-flight,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.893-902, 2016. 10.1109\/cvpr.2016.103","DOI":"10.1109\/CVPR.2016.103"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] Q. Guo, I. Frosio, O. Gallo, T. Zickler, and J. Jautz, \u201cTackling 3D ToF artifacts through learning and the flat dataset,\u201d The European Conference on Computer Vision (ECCV), pp.368-383, 2018.","DOI":"10.1007\/978-3-030-01246-5_23"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] F. Heide, L. Xiao, A. Kolb, M.B. Hullin, and W. Heidrich, \u201cImaging in scattering media using correlation image sensors and sparse convolutional coding,\u201d Optics Express, vol.22, no.21, pp.26338-26350, 2014. 10.1364\/oe.22.026338","DOI":"10.1364\/OE.22.026338"},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] G. Satat, M. Tancik, and R. Rasker, \u201cTowards photography through realistic fog,\u201d The IEEE International Conference on Computational Photography (ICCP), pp.1-10, 2018. 10.1109\/iccphot.2018.8368463","DOI":"10.1109\/ICCPHOT.2018.8368463"},{"key":"31","doi-asserted-by":"publisher","unstructured":"[31] F. Heide, M.B. Hullin, J. Gregson, and W. Heidrich, \u201cLow-budget transient imaging using photonic mixer devices,\u201d ACM Transactions on Graphics (TOG), vol.32, no.4, 2013. 10.1145\/2461912.2461945","DOI":"10.1145\/2461912.2461945"},{"key":"32","doi-asserted-by":"publisher","unstructured":"[32] T. Muraji, K. Tanaka, T. Funatomi, and Y. Mukaigawa, \u201cDepth from phasor distortions in fog,\u201d Optics Express, vol.27, no.13, pp.18858-18868, 2019. 10.1364\/oe.27.018858","DOI":"10.1364\/OE.27.018858"},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] S.G. Narasimhan, M. Gupta, C. Donner, R. Ramamoorthi, S.K.Nayar, and H.W. Jensen, \u201cAcquiring scattering properties of participating media by dilution,\u201d ACM Transaction on Graphics, vol.25, no.3, pp.1003-1012, 2006. 10.1145\/1141911.1141986","DOI":"10.1145\/1141911.1141986"},{"key":"34","doi-asserted-by":"publisher","unstructured":"[34] M. Gupta, S.K. Nayar, M.B. Hullin, and J. Martin, \u201cPhasor imaging: A generalization of correlation-based time-of-flight imaging,\u201d ACM Transaction on Graphics (TOG), vol.34, no.5, 2015. 10.1145\/2735702","DOI":"10.1145\/2735702"},{"key":"35","doi-asserted-by":"publisher","unstructured":"[35] A.E. Beaton and J.W. Tukey, \u201cThe fitting of power series, meaning polynomials, illustrated on band-spectroscopic data,\u201d Technometrics, vol.16, no.2, pp.147-185, 1974. 10.1080\/00401706.1974.10489171","DOI":"10.1080\/00401706.1974.10489171"},{"key":"36","doi-asserted-by":"publisher","unstructured":"[36] P.J. Huber, \u201cRobust regression: Asymptotics, conjectures and monte carlo,\u201d The Annals of Statistics, vol.1, no.5, pp.799-821, 1973. 10.1214\/aos\/1176342503","DOI":"10.1214\/aos\/1176342503"},{"key":"37","unstructured":"[37] C.M. Bishop, Pattern Recognition and Machine Intelligence, Springer, 2006."},{"key":"38","doi-asserted-by":"crossref","unstructured":"[38] K.N. Chaudhury and A. Singer, \u201cNon-local patch regression: Robust image denoising in patch space,\u201d The IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1345-1349, 2013. 10.1109\/icassp.2013.6637870","DOI":"10.1109\/ICASSP.2013.6637870"},{"key":"39","doi-asserted-by":"crossref","unstructured":"[39] K. Tanaka, Y. Mukaigawa, T. Funatomi, H. Kubo, Y. Matsushita, and Y. Yagi, \u201cMaterial classification using frequency- and depth-dependent time-of-flight distortion,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.79-88, 2017. 10.1109\/cvpr.2017.293","DOI":"10.1109\/CVPR.2017.293"},{"key":"40","unstructured":"[40] S.G. Narasimhan and S.K. Nayar, \u201cShedding light on the weather,\u201d The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.665-672, 2003. 10.1109\/cvpr.2003.1211417"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/3\/E103.D_2019EDP7219\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T10:53:57Z","timestamp":1722509637000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/3\/E103.D_2019EDP7219\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,1]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2019edp7219","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,1]]}}}