{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T07:05:54Z","timestamp":1763535954999,"version":"3.37.3"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T00:00:00Z","timestamp":1643328000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T00:00:00Z","timestamp":1643328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Tianjin Intelligent Security Industry Chain Technology Adaptation and Application Project","award":["18ZXZNGX00320"],"award-info":[{"award-number":["18ZXZNGX00320"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s11760-021-02093-z","type":"journal-article","created":{"date-parts":[[2022,1,28]],"date-time":"2022-01-28T00:04:41Z","timestamp":1643328281000},"page":"1409-1416","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Low-light image enhancement based on normal-light image degradation"],"prefix":"10.1007","volume":"16","author":[{"given":"Bai","family":"Zhao","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3932-9228","authenticated-orcid":false,"given":"Xiaolin","family":"Gong","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lingchao","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,28]]},"reference":[{"issue":"4","key":"2093_CR1","doi-asserted-by":"publisher","first-page":"2049","DOI":"10.1109\/TIP.2018.2794218","volume":"27","author":"J Cai","year":"2018","unstructured":"Cai, J., Gu, S., Zhang, L.: Learning a deep single image contrast enhancer from multi-exposure images. IEEE Trans. Image Process. 27(4), 2049\u20132062 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"2093_CR2","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.neucom.2021.05.025","volume":"454","author":"Z Jiang","year":"2021","unstructured":"Jiang, Z., Li, H., Liu, L., Men, H., Wang, H.: A switched view of Retinex: deep self-regularized low-light image enhancement. Neurocomputing 454, 361\u2013372 (2021)","journal-title":"Neurocomputing"},{"issue":"4","key":"2093_CR3","doi-asserted-by":"publisher","first-page":"1153","DOI":"10.1007\/s11263-020-01418-8","volume":"129","author":"J Liu","year":"2021","unstructured":"Liu, J., Xu, D., Yang, W., Fan, M., Huang, H.: Benchmarking low-light image enhancement and beyond. Int. J. Comput. Vision 129(4), 1153\u20131184 (2021)","journal-title":"Int. J. Comput. Vision"},{"issue":"7","key":"2093_CR4","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1007\/s11760-014-0626-7","volume":"9","author":"MH Asmare","year":"2015","unstructured":"Asmare, M.H., Asirvadam, V.S., Hani, A.F.M.: Image enhancement based on contourlet transform. SIViP 9(7), 1679\u20131690 (2015)","journal-title":"SIViP"},{"key":"2093_CR5","doi-asserted-by":"crossref","unstructured":"Chen, C., Chen, Q., Xu, J., Koltun, V.: Learning to see in the dark. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3291\u20133300 (2018)","DOI":"10.1109\/CVPR.2018.00347"},{"key":"2093_CR6","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.ins.2019.05.015","volume":"496","author":"W Wang","year":"2019","unstructured":"Wang, W., Chen, Z., Yuan, X., Wu, X.: Adaptive image enhancement method for correcting low-illumination images. Inf. Sci. 496, 25\u201341 (2019)","journal-title":"Inf. Sci."},{"issue":"2","key":"2093_CR7","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1016\/j.dsp.2003.07.002","volume":"14","author":"HD Cheng","year":"2004","unstructured":"Cheng, H.D., Shi, X.J.: A simple and effective histogram equalization approach to image enhancement. Digit. Signal Process. 14(2), 158\u2013170 (2004)","journal-title":"Digit. Signal Process."},{"issue":"2","key":"2093_CR8","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1109\/TCE.2007.381734","volume":"53","author":"M Abdullah-Al-Wadud","year":"2007","unstructured":"Abdullah-Al-Wadud, M., Kabir, M.H., Dewan, M.A.A., Chae, O.: A dynamic histogram equalization for image contrast enhancement. IEEE Trans. Consum. Electron. 53(2), 593\u2013600 (2007)","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"6","key":"2093_CR9","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1038\/scientificamerican1277-108","volume":"237","author":"EH Land","year":"1977","unstructured":"Land, E.H.: The Retinex theory of color vision. Sci. Am. 237(6), 108\u2013129 (1977)","journal-title":"Sci. Am."},{"issue":"7","key":"2093_CR10","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1109\/83.597272","volume":"6","author":"DJ Jobson","year":"1997","unstructured":"Jobson, D.J., Rahman, Z., Woodell, G.A.: A multiscale Retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans. Image Process. 6(7), 965\u2013976 (1997)","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"2093_CR11","doi-asserted-by":"publisher","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","volume":"26","author":"X Guo","year":"2016","unstructured":"Guo, X., Li, Y., Ling, H.: LIME: low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982\u2013993 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"2093_CR12","doi-asserted-by":"crossref","unstructured":"Yang, J., Xu, Y., Yue, H., Jiang, Z., Li, K.: Low-light image enhancement based on Retinex decomposition and adaptive gamma correction. IET Image Process. 15(5), 1189\u20131202 (2021)","DOI":"10.1049\/ipr2.12097"},{"key":"2093_CR13","doi-asserted-by":"crossref","unstructured":"Song, X., Huang, J., Cao, J., Song, D.: Multi-scale joint network based on Retinex theory for low-light enhancement. Signal Image Video Process. 15, 1257\u20131264 (2021)","DOI":"10.1007\/s11760-021-01856-y"},{"issue":"1","key":"2093_CR14","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1007\/s11760-018-1345-2","volume":"13","author":"X Jiang","year":"2019","unstructured":"Jiang, X., Yao, H., Liu, D.: Nighttime image enhancement based on image decomposition. SIViP 13(1), 189\u2013197 (2019)","journal-title":"SIViP"},{"key":"2093_CR15","unstructured":"Ying, Z., Li, G., Gao, W.: A bio-inspired multi-exposure fusion framework for low-light image enhancement (2017). arXiv preprint arXiv:1711.00591"},{"issue":"4","key":"2093_CR16","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1109\/TCSVT.2018.2828141","volume":"29","author":"Y Ren","year":"2018","unstructured":"Ren, Y., Ying, Z., Li, T.H., Li, G.: LECARM: low-light image enhancement using the camera response model. IEEE Trans. Circuits Syst. Video Technol. 29(4), 968\u2013981 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"2093_CR17","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.sigpro.2016.05.031","volume":"129","author":"X Fu","year":"2016","unstructured":"Fu, X., Zeng, D., Huang, Y., Liao, Y., Ding, X., Paisley, J.: A fusion-based enhancing method for weakly illuminated images. Signal Process. 129, 82\u201396 (2016)","journal-title":"Signal Process."},{"key":"2093_CR18","doi-asserted-by":"crossref","unstructured":"Guo, C., Li, C., Guo, J., Loy, C. C., Hou, J., Kwong, S., Cong, R.: Zero reference deep curve estimation for low-light image enhancement. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"2093_CR19","unstructured":"Wei, C., Wang, W., Yang, W., Liu, J.: Deep retinex decomposition for low-light enhancement. In: Proceeding of British Machine Vision Conference, pp. 1\u201312 (2018)"},{"issue":"10","key":"2093_CR20","doi-asserted-by":"publisher","first-page":"3583","DOI":"10.3390\/s18103583","volume":"18","author":"S Ma","year":"2018","unstructured":"Ma, S., Ma, H., Xu, Y., Li, S., Lv, C., Zhu, M.: A low-light sensor image enhancement algorithm based on HSI color model. Sensors 18(10), 3583 (2018)","journal-title":"Sensors"},{"key":"2093_CR21","doi-asserted-by":"publisher","first-page":"74306","DOI":"10.1109\/ACCESS.2020.2988767","volume":"8","author":"W Huang","year":"2020","unstructured":"Huang, W., Zhu, Y., Huang, R.: Low light image enhancement network with attention mechanism and Retinex model. IEEE Access 8, 74306\u201374314 (2020)","journal-title":"IEEE Access"},{"key":"2093_CR22","doi-asserted-by":"crossref","unstructured":"Wang, W., Wei, C., Yang, W., Liu, J.: GLADNet: Lowlight enhancement network with global awareness. In: Proceeding of IEEE International Conference on Automatic Face & Gesture Recognition, pp. 751\u2013755 (2018)","DOI":"10.1109\/FG.2018.00118"},{"key":"2093_CR23","doi-asserted-by":"crossref","unstructured":"Atoum, Y., Ye, M., Ren, L.: Color-wise attention network for low-light image enhancement. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 506\u2013507 (2020)","DOI":"10.1109\/CVPRW50498.2020.00261"},{"key":"2093_CR24","doi-asserted-by":"publisher","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","volume":"30","author":"Y Jiang","year":"2019","unstructured":"Jiang, Y., Gong, X., Liu, D., Cheng, Y., Fang, C., Shen, X., Yang, J., Zhou, P., Wang, Z.: EnlightenGAN: deep light enhancement without paired supervision. IEEE Trans. Image Process. 30, 2340\u20132349 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"2093_CR25","doi-asserted-by":"crossref","unstructured":"Hua, W., Xia, Y.: Low-Light Image enhancement based on joint generative adversarial network and image quality assessment. In: Proceeding of International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, pp. 1\u20136 (2018)","DOI":"10.1109\/CISP-BMEI.2018.8633150"},{"key":"2093_CR26","doi-asserted-by":"crossref","unstructured":"Cheng, Y., Yan, J., Wang, Z.: Enhancement of weakly illuminated images by deep fusion networks. In: Proceeding of IEEE International Conference on Image Processing, pp. 924\u2013928 (2019)","DOI":"10.1109\/ICIP.2019.8803041"},{"issue":"4","key":"2093_CR27","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"2093_CR28","doi-asserted-by":"crossref","unstructured":"Mittal, A., Soundararajan, R., Bovik, A.C.: Making a \u2018completely blind\u2019 image quality analyzer. IEEE Signal Process. Lett. 20(3), 209\u2013212 (2013)","DOI":"10.1109\/LSP.2012.2227726"},{"key":"2093_CR29","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: Convolutional networks for biomedical image segmentation. In: Proceeding of Medical Image Computing and Computer-Assisted Intervention, pp. 234\u2013241 (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"2093_CR30","doi-asserted-by":"crossref","unstructured":"Sun, K., Xiao, B., Liu, D., Wang, J.: Deep high-resolution representation learning for human pose estimation. In: Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, pp. 5693\u20135703 (2019)","DOI":"10.1109\/CVPR.2019.00584"},{"key":"2093_CR31","unstructured":"Lv, F., Lu, F., Wu, J., Lim, C.: MBLLEN: Low-light imagevideo enhancement using CNNs. In: Proceeding of British Machine Vision Conference, pp. 1\u201313 (2018)"},{"key":"2093_CR32","doi-asserted-by":"crossref","unstructured":"Lee, C., Lee, C., Kim, C. S.: Contrast enhancement based on layered difference representation. In: Proceeding of IEEE International Conference on Image Processing, pp. 965\u2013968 (2012)","DOI":"10.1109\/ICIP.2012.6467022"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-02093-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-021-02093-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-021-02093-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,19]],"date-time":"2022-05-19T06:21:07Z","timestamp":1652941267000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-021-02093-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,28]]},"references-count":32,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["2093"],"URL":"https:\/\/doi.org\/10.1007\/s11760-021-02093-z","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2022,1,28]]},"assertion":[{"value":"27 May 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 November 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 January 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}