{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T23:10:09Z","timestamp":1751411409067,"version":"3.41.0"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2018,2,20]],"date-time":"2018-02-20T00:00:00Z","timestamp":1519084800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61572096","61733002"],"award-info":[{"award-number":["61572096","61733002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61432003","61720106005"],"award-info":[{"award-number":["61432003","61720106005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2019,4]]},"DOI":"10.1007\/s00371-018-1485-y","type":"journal-article","created":{"date-parts":[[2018,2,20]],"date-time":"2018-02-20T03:59:56Z","timestamp":1519099196000},"page":"565-577","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Fast example searching for input-adaptive data-driven dehazing with Gaussian process regression"],"prefix":"10.1007","volume":"35","author":[{"given":"Xin","family":"Fan","sequence":"first","affiliation":[]},{"given":"Xianxuan","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Minjun","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Zhongxuan","family":"Luo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,2,20]]},"reference":[{"key":"1485_CR1","doi-asserted-by":"crossref","unstructured":"Ancuti, C.O., Ancuti, C., Hermans, C., Bekaert, P.: A fast semi-inverse approach to detect and remove the haze from a single image. In: Asian Conference on Computer Vision, pp. 501\u2013514. Springer (2011)","DOI":"10.1007\/978-3-642-19309-5_39"},{"key":"1485_CR2","volume-title":"Pattern Recognition and Machine Learning","author":"CM Bishop","year":"2006","unstructured":"Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Berlin (2006)"},{"key":"1485_CR3","doi-asserted-by":"crossref","unstructured":"Burger, H.C., Schuler, C.J., Harmeling, S.: Image denoising: can plain neural networks compete with BM3D? In: Computer Vision and Pattern Recognition, pp. 2392\u20132399. IEEE (2012)","DOI":"10.1109\/CVPR.2012.6247952"},{"key":"1485_CR4","doi-asserted-by":"crossref","unstructured":"Cai, B., Xu, X., Jia, K., Qing, C., Tao, D.: Dehazenet: an end-to-end system for single image haze removal. arXiv preprint arXiv:1601.07661 (2016)","DOI":"10.1109\/TIP.2016.2598681"},{"key":"1485_CR5","unstructured":"Cao, Y., Brubaker, M.A., Fleet, D.J., Hertzmann, A.: Efficient optimization for sparse Gaussian process regression. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2013)"},{"key":"1485_CR6","unstructured":"Chen, L., Lu, G., Zhang, D.: Effects of different Gabor filter parameters on image retrieval by texture. In: ACM International Conference Multimedia, pp. 273\u2013278. Citeseer (2004)"},{"key":"1485_CR7","doi-asserted-by":"crossref","unstructured":"Crete, F., Dolmiere, T., Ladret, P., Nicolas, M.: The blur effect: perception and estimation with a new no-reference perceptual blur metric. In: Rogowitz, BE., Pappas, TN., Daly, SJ. (eds.) Electronic Imaging 2007, pp. 64,920I\u201364,920I. International Society for Optics and Photonics (2007)","DOI":"10.1117\/12.702790"},{"issue":"10","key":"1485_CR8","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2347736.2347755","volume":"55","author":"P Domingos","year":"2012","unstructured":"Domingos, P.: A few useful things to know about machine learning. Commun. ACM 55(10), 78\u201387 (2012)","journal-title":"Commun. ACM"},{"key":"1485_CR9","doi-asserted-by":"publisher","unstructured":"Fan, X., Gao, R., Wang, Y.: Example-based haze removal with two-layer Gaussian process regressions. In: Keyser, J., Kim, Y.J., Wonka, P. (eds.) Pacific Graphics Short Papers. The Eurographics Association (2014). https:\/\/doi.org\/10.2312\/pgs.20141260","DOI":"10.2312\/pgs.20141260"},{"key":"1485_CR10","doi-asserted-by":"crossref","unstructured":"Fan, X., Liu, R., Huyan, K., Feng, Y., Luo, Z.: Self-reinforced cascaded regression for face alignment. In: AAAI (2018)","DOI":"10.1609\/aaai.v32i1.12249"},{"key":"1485_CR11","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s00371-015-1083-1","volume":"32","author":"X Fan","year":"2016","unstructured":"Fan, X., Wang, Y., Gao, R., Luo, Z.: Haze editing with natural transformations. Vis. Comput. 32, 137\u2013147 (2016)","journal-title":"Vis. Comput."},{"key":"1485_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2592328","author":"X Fan","year":"2016","unstructured":"Fan, X., Wang, Y., Tang, X., Gao, R., Luo, Z.: Two-layer Gaussian process regression with example selection for image dehazing. IEEE Trans. Circuits Syst. Video Technol. (2016). https:\/\/doi.org\/10.1109\/TCSVT.2016.2592328","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"3","key":"1485_CR13","doi-asserted-by":"publisher","first-page":"72:1","DOI":"10.1145\/1360612.1360671","volume":"27","author":"R Fattal","year":"2008","unstructured":"Fattal, R.: Single image dehazing. ACM Trans. Graph. 27(3), 72:1\u201372:9 (2008). https:\/\/doi.org\/10.1145\/1360612.1360671","journal-title":"ACM Trans. Graph."},{"key":"1485_CR14","doi-asserted-by":"crossref","unstructured":"Feng, Y., Liu, R., Fan, X., Huyan, K., Luo, Z.: Leveraging geometric correlation for input-adaptive facial landmark regression. In: IEEE International Conference on Multimedia and Expo (ICME), pp. 385\u2013390 (2017)","DOI":"10.1109\/ICME.2017.8019469"},{"issue":"2","key":"1485_CR15","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/38.988747","volume":"22","author":"WT Freeman","year":"2002","unstructured":"Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-based super-resolution. Comput. Graph. Appl. 22(2), 56\u201365 (2002)","journal-title":"Comput. Graph. Appl."},{"issue":"1","key":"1485_CR16","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1023\/A:1026501619075","volume":"40","author":"WT Freeman","year":"2000","unstructured":"Freeman, W.T., Pasztor, E.C., Carmichael, O.T.: Learning low-level vision. Int. J. Comput. Vis. 40(1), 25\u201347 (2000)","journal-title":"Int. J. Comput. Vis."},{"issue":"3","key":"1485_CR17","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1016\/j.tics.2014.12.010","volume":"19","author":"R Frost","year":"2015","unstructured":"Frost, R., Armstrong, B.C., Siegelman, N., Christiansen, M.H.: Domain generality versus modality specificity: the paradox of statistical learning. Trends Cogn. Sci. 19(3), 117\u2013125 (2015)","journal-title":"Trends Cogn. Sci."},{"key":"1485_CR18","doi-asserted-by":"crossref","unstructured":"Gibson, K., Belongie, S., Nguyen, T.: Example based depth from fog. In: International Conference on Image Processing, pp. 728\u2013732. IEEE (2013)","DOI":"10.1109\/ICIP.2013.6738150"},{"key":"1485_CR19","doi-asserted-by":"crossref","unstructured":"Gibson, K.B., Belongie, S.J., Nguyen, T.Q.: Example based depth from fog. In: International Conference on Image Processing, pp. 728\u2013732. IEEE (2013)","DOI":"10.1109\/ICIP.2013.6738150"},{"key":"1485_CR20","doi-asserted-by":"crossref","unstructured":"He, H., Siu, W.C.: Single image super-resolution using Gaussian process regression. In: Computer Vision and Pattern Recognition, pp. 449\u2013456 (2011)","DOI":"10.1109\/CVPR.2011.5995713"},{"key":"1485_CR21","doi-asserted-by":"publisher","unstructured":"He, K., Sun, J., Tang, X.: Guided image filtering. In: European Conference on Computer Vision, vol. 35(6), pp. 1397\u20131409 (2011). https:\/\/doi.org\/10.1109\/TPAMI.2012.213","DOI":"10.1109\/TPAMI.2012.213"},{"issue":"12","key":"1485_CR22","doi-asserted-by":"publisher","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","volume":"33","author":"K He","year":"2012","unstructured":"He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341\u20132353 (2012). https:\/\/doi.org\/10.1109\/TPAMI.2010.168","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"13","key":"1485_CR23","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image\/video quality assessment. Electron. Lett. 44(13), 800\u2013801 (2008)","journal-title":"Electron. Lett."},{"key":"1485_CR24","doi-asserted-by":"crossref","unstructured":"Jegou, H., Douze, M., Schmid, C.: Hamming embedding and weak geometric consistency for large scale image search. In: European Conference on Computer Vision, pp. 304\u2013317. Springer (2008)","DOI":"10.1007\/978-3-540-88682-2_24"},{"issue":"9","key":"1485_CR25","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1109\/TPAMI.2015.2389797","volume":"37","author":"Y Kwon","year":"2015","unstructured":"Kwon, Y., Kim, K.I., Tompkin, J., Kim, J.H., Theobalt, C.: Efficient learning of image super-resolution and compression artifact removal with semi-local Gaussian processes. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1792\u20131805 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1485_CR26","first-page":"1865","volume":"11","author":"M Lazarogredilla","year":"2010","unstructured":"Lazarogredilla, M., Quinonerocandela, J., Rasmussen, C.E., Figueirasvidal, A.R.: Sparse spectrum Gaussian process regression. J. Mach. Learn. Res. 11, 1865\u20131881 (2010)","journal-title":"J. Mach. Learn. Res."},{"key":"1485_CR27","doi-asserted-by":"crossref","unstructured":"Ren, W., Liu, S., Zhang, H., Pan, J., Cao, X., Yang, M.H.: Single image dehazing via multi-scale convolutional neural networks. In: European Conference on Computer Vision (2016)","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"1485_CR28","doi-asserted-by":"crossref","unstructured":"Ren, X., Malik, J.: Learning a classification model for segmentation. In: International Conference on Computer Vision, pp. 10\u201317. IEEE (2003)","DOI":"10.1109\/ICCV.2003.1238308"},{"key":"1485_CR29","doi-asserted-by":"crossref","unstructured":"Saxena, A., Sun, M., Ng, A.Y.: Learning 3-d scene structure from a single still image. In: International Conference on Computer Vision (2007)","DOI":"10.1109\/ICCV.2007.4408828"},{"key":"1485_CR30","doi-asserted-by":"crossref","unstructured":"Schmidt, U., Rother, C., Nowozin, S., Jancsary, J., Roth, S.: Discriminative non-blind deblurring. In: Computer Vision and Pattern Recognition, pp. 604\u2013611 (2013)","DOI":"10.1109\/CVPR.2013.84"},{"key":"1485_CR31","unstructured":"Settles, B.: Active Learning Literature Survey. Computer Sciences Technical Report 1648. University of Wisconsin-Madison (2010)"},{"key":"1485_CR32","doi-asserted-by":"crossref","unstructured":"Silpaanan, C., Hartley, R.: Optimised kd-trees for fast image descriptor matching. In: Computer Vision and Pattern Recognition, pp. 1\u20138. IEEE (2008)","DOI":"10.1109\/CVPR.2008.4587638"},{"key":"1485_CR33","doi-asserted-by":"crossref","unstructured":"Sun, L., Hays, J.: Super-resolution from internet-scale scene matching. In: International Conference on Computational Photography, pp. 1\u201312. IEEE (2012)","DOI":"10.1109\/ICCPhot.2012.6215221"},{"key":"1485_CR34","doi-asserted-by":"publisher","unstructured":"Tan, R.: Visibility in bad weather from a single image. In: Computer Vision and Pattern Recognition, pp. 1\u20138 (2008). https:\/\/doi.org\/10.1109\/CVPR.2008.4587643","DOI":"10.1109\/CVPR.2008.4587643"},{"key":"1485_CR35","doi-asserted-by":"crossref","unstructured":"Tang, K., Yang, J., Wang, J.: Investigating haze-relevant features in a learning framework for image dehazing. In: Computer Vision and Pattern Recognition (2014)","DOI":"10.1109\/CVPR.2014.383"},{"key":"1485_CR36","doi-asserted-by":"crossref","unstructured":"Tang, X., Fan, X., Duan, Y., Luo, Z.: A fast training example searching algorithm for data-driven dehazing. In: International Conference on Digital Home (2016)","DOI":"10.1109\/ICDH.2016.010"},{"key":"1485_CR37","doi-asserted-by":"crossref","unstructured":"Yue, H., Sun, X., Yang, J., Wu, F.: CID: Combined image denoising in spatial and frequency domains using web images. In: Computer Vision and Pattern Recognition, pp. 2933\u20132940 (2014)","DOI":"10.1109\/CVPR.2014.375"},{"issue":"2","key":"1485_CR38","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1109\/TCSVT.2014.2347513","volume":"25","author":"X Zhao","year":"2015","unstructured":"Zhao, X., Wang, S., Li, S., Li, J.: Passive image-splicing detection by a 2-d noncausal Markov model. IEEE Trans. Circuits Syst. Video Technol. 25(2), 185\u2013199 (2015)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"11","key":"1485_CR39","doi-asserted-by":"publisher","first-page":"3522","DOI":"10.1109\/TIP.2015.2446191","volume":"24","author":"Q Zhu","year":"2015","unstructured":"Zhu, Q., Mai, J., Shao, L.: A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Process. 24(11), 3522\u20133533 (2015)","journal-title":"IEEE Trans. Image Process."},{"key":"1485_CR40","doi-asserted-by":"crossref","unstructured":"Zoran, D., Isola, P., Krishnan, D., Freeman, W.T.: Learning ordinal relationships for mid-level vision. In: International Conference on Computer Vision, pp. 388\u2013396 (2015)","DOI":"10.1109\/ICCV.2015.52"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00371-018-1485-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-018-1485-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-018-1485-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T22:33:10Z","timestamp":1751409190000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00371-018-1485-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,20]]},"references-count":40,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2019,4]]}},"alternative-id":["1485"],"URL":"https:\/\/doi.org\/10.1007\/s00371-018-1485-y","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2018,2,20]]},"assertion":[{"value":"20 February 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}