{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:05:22Z","timestamp":1760101522674,"version":"3.40.4"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T00:00:00Z","timestamp":1729209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"publisher","award":["2022-KF-12-14"],"award-info":[{"award-number":["2022-KF-12-14"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Education Reform Project of Liaoning Province","award":["LNYJG2022493"],"award-info":[{"award-number":["LNYJG2022493"]}]},{"name":"Interdisciplinary Project of Dalian University","award":["DLUXK-2024-YB-001"],"award-info":[{"award-number":["DLUXK-2024-YB-001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s00371-024-03642-6","type":"journal-article","created":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T20:29:33Z","timestamp":1729283373000},"page":"4001-4016","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["TFFD-Net: an effective two-stage mixed feature fusion and detail recovery dehazing network"],"prefix":"10.1007","volume":"41","author":[{"given":"Chen","family":"Li","sequence":"first","affiliation":[]},{"given":"Weiqi","family":"Yan","sequence":"additional","affiliation":[]},{"given":"Hongwei","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Shihua","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Yueping","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,18]]},"reference":[{"issue":"1","key":"3642_CR1","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/TCSVT.2023.3274366","volume":"34","author":"G Zhang","year":"2023","unstructured":"Zhang, G., Fang, W., Zheng, Y., Wang, R.: SDBAD-Net: a spatial dual-branch attention dehazing network based on meta-former paradigm. IEEE Trans. Circuits Syst. Video Technol. 34(1), 60\u201370 (2023). https:\/\/doi.org\/10.1109\/TCSVT.2023.3274366","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"3642_CR2","doi-asserted-by":"publisher","unstructured":"Chen, C.-F.R., Fan, Q., Panda, R.: CrossViT: cross-attention multi-scale vision transformer for image classification. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 357\u2013366 (2021). https:\/\/doi.org\/10.1109\/iccv48922.2021.00041","DOI":"10.1109\/iccv48922.2021.00041"},{"key":"3642_CR3","doi-asserted-by":"publisher","first-page":"6756","DOI":"10.1109\/TMM.2022.3214431","volume":"25","author":"C Zhang","year":"2022","unstructured":"Zhang, C., Bai, H., Zhao, Y.: Fine-grained image classification by class and image-specific decomposition with multiple views. IEEE Trans. Multimed. 25, 6756\u20136766 (2022). https:\/\/doi.org\/10.1109\/TMM.2022.3214431","journal-title":"IEEE Trans. Multimed."},{"issue":"5","key":"3642_CR4","doi-asserted-by":"publisher","first-page":"1182","DOI":"10.1007\/s11263-019-01182-4","volume":"128","author":"D Dai","year":"2020","unstructured":"Dai, D., Sakaridis, C., Hecker, S., Van Gool, L.: Curriculum model adaptation with synthetic and real data for semantic foggy scene understanding. Int. J. Comput. Vis. 128(5), 1182\u20131204 (2020). https:\/\/doi.org\/10.1007\/s11263-019-01182-4","journal-title":"Int. J. Comput. Vis."},{"issue":"11","key":"3642_CR5","doi-asserted-by":"publisher","first-page":"12760","DOI":"10.1109\/tpami.2022.3202765","volume":"45","author":"Y-H Wu","year":"2022","unstructured":"Wu, Y.-H., Liu, Y., Zhan, X., Cheng, M.-M.: P2T: pyramid pooling transformer for scene understanding. IEEE Trans. Pattern Anal. Mach. Intell. 45(11), 12760\u201312771 (2022). https:\/\/doi.org\/10.1109\/tpami.2022.3202765","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"8","key":"3642_CR6","doi-asserted-by":"publisher","first-page":"5122","DOI":"10.1109\/TNNLS.2021.3125679","volume":"34","author":"S-C Huang","year":"2022","unstructured":"Huang, S.-C., Hoang, Q.-V., Le, T.-H.: SFA-Net: a selective features absorption network for object detection in rainy weather conditions. IEEE Trans. Neural Netw. Learn. Syst. 34(8), 5122\u20135132 (2022). https:\/\/doi.org\/10.1109\/TNNLS.2021.3125679","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"4","key":"3642_CR7","doi-asserted-by":"publisher","first-page":"045406","DOI":"10.1088\/1361-6501\/acb075","volume":"34","author":"L Shen","year":"2023","unstructured":"Shen, L., Tao, H., Ni, Y., Wang, Y., Stojanovic, V.: Improved YOLOv3 model with feature map cropping for multi-scale road object detection. Meas. Sci. Technol. 34(4), 045406 (2023). https:\/\/doi.org\/10.1088\/1361-6501\/acb075","journal-title":"Meas. Sci. Technol."},{"key":"3642_CR8","doi-asserted-by":"publisher","first-page":"104859","DOI":"10.1016\/j.imavis.2023.104859","volume":"140","author":"R Jaisurya","year":"2023","unstructured":"Jaisurya, R., Mukherjee, S.: AGLC-GAN: attention-based global-local cycle-consistent generative adversarial networks for unpaired single image dehazing. Image Vis. Comput. 140, 104859 (2023). https:\/\/doi.org\/10.1016\/j.imavis.2023.104859","journal-title":"Image Vis. Comput."},{"issue":"2","key":"3642_CR9","doi-asserted-by":"publisher","first-page":"57","DOI":"10.3390\/info8020057","volume":"8","author":"X Yuan","year":"2017","unstructured":"Yuan, X., Ju, M., Gu, Z., Wang, S.: An effective and robust single image dehazing method using the dark channel prior. Information 8(2), 57 (2017). https:\/\/doi.org\/10.3390\/info8020057","journal-title":"Information"},{"key":"3642_CR10","doi-asserted-by":"publisher","first-page":"3089","DOI":"10.1109\/tmm.2022.3155937","volume":"25","author":"C Lin","year":"2022","unstructured":"Lin, C., Rong, X., Yu, X.: MSAFF-Net: multiscale attention feature fusion networks for single image dehazing and beyond. IEEE Trans. Multimed. 25, 3089\u20133100 (2022). https:\/\/doi.org\/10.1109\/tmm.2022.3155937","journal-title":"IEEE Trans. Multimed."},{"key":"3642_CR11","volume-title":"Optics of the Atmosphere: Scattering by Molecules and Particles","author":"EJ McCartney","year":"1976","unstructured":"McCartney, E.J.: Optics of the Atmosphere: Scattering by Molecules and Particles. Wiley, New York (1976)"},{"key":"3642_CR12","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1023\/A:1016328200723","volume":"48","author":"SG Narasimhan","year":"2002","unstructured":"Narasimhan, S.G., Nayar, S.K.: Vision and the atmosphere. Int. J. Comput. Vis. 48, 233\u2013254 (2002). https:\/\/doi.org\/10.1023\/A:1016328200723","journal-title":"Int. J. Comput. Vis."},{"key":"3642_CR13","doi-asserted-by":"publisher","first-page":"103984","DOI":"10.1016\/j.jvcir.2023.103984","volume":"97","author":"X Xie","year":"2023","unstructured":"Xie, X., Li, C., Guan, T., Zheng, Y., Wu, X.: A novel complex-valued convolutional network for real-world single image dehazing. J. Vis. Commun. Image Represent. 97, 103984 (2023). https:\/\/doi.org\/10.1016\/j.jvcir.2023.103984","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"12","key":"3642_CR14","first-page":"2341","volume":"33","author":"K He","year":"2010","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 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3642_CR15","doi-asserted-by":"publisher","first-page":"102416","DOI":"10.1016\/j.displa.2023.102416","volume":"78","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Chen, J., Lu, P., Zhu, C., Jian, Y., Sun, C., Liang, H.: MFID-Net: multi-scaled feature-fused image dehazing via dynamic weights. Displays 78, 102416 (2023). https:\/\/doi.org\/10.1016\/j.displa.2023.102416","journal-title":"Displays"},{"issue":"11","key":"3642_CR16","doi-asserted-by":"publisher","first-page":"5187","DOI":"10.1109\/tip.2016.2598681","volume":"25","author":"B Cai","year":"2016","unstructured":"Cai, B., Xu, X., Jia, K., Qing, C., Tao, D.: DehazeNet: an end-to-end system for single image haze removal. IEEE Trans. Image Process. 25(11), 5187\u20135198 (2016). https:\/\/doi.org\/10.1109\/tip.2016.2598681","journal-title":"IEEE Trans. Image Process."},{"key":"3642_CR17","doi-asserted-by":"publisher","unstructured":"Qu, Y., Chen, Y., Huang, J., Xie, Y.: Enhanced Pix2pix dehazing network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8160\u20138168 (2019). https:\/\/doi.org\/10.1109\/cvpr.2019.00835","DOI":"10.1109\/cvpr.2019.00835"},{"key":"3642_CR18","doi-asserted-by":"publisher","unstructured":"Liu, X., Ma, Y., Shi, Z., Chen, J.: GridDehazeNet: attention-based multi-scale network for image dehazing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7314\u20137323 (2019). https:\/\/doi.org\/10.1109\/iccv.2019.00741","DOI":"10.1109\/iccv.2019.00741"},{"issue":"2","key":"3642_CR19","doi-asserted-by":"publisher","first-page":"510","DOI":"10.1109\/tcsvt.2021.3067062","volume":"32","author":"X Zhang","year":"2021","unstructured":"Zhang, X., Wang, J., Wang, T., Jiang, R.: Hierarchical feature fusion with mixed convolution attention for single image dehazing. IEEE Trans. Circuits Syst. Video Technol. 32(2), 510\u2013522 (2021). https:\/\/doi.org\/10.1109\/tcsvt.2021.3067062","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"10","key":"3642_CR20","doi-asserted-by":"publisher","first-page":"7719","DOI":"10.1109\/TNNLS.2022.3146004","volume":"34","author":"Y Zhou","year":"2022","unstructured":"Zhou, Y., Chen, Z., Li, P., Song, H., Chen, C.P., Sheng, B.: FSAD-Net: feedback spatial attention dehazing network. IEEE Trans. Neural Netw. Learn. Syst. 34(10), 7719\u20137733 (2022). https:\/\/doi.org\/10.1109\/TNNLS.2022.3146004","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"3642_CR21","doi-asserted-by":"publisher","first-page":"102137","DOI":"10.1016\/j.displa.2021.102137","volume":"72","author":"H Zhou","year":"2022","unstructured":"Zhou, H., Zhao, Z., Xiong, H., Liu, Y.: A unified weighted variational model for simultaneously haze removal and noise suppression of hazy images. Displays 72, 102137 (2022). https:\/\/doi.org\/10.1016\/j.displa.2021.102137","journal-title":"Displays"},{"key":"3642_CR22","doi-asserted-by":"publisher","unstructured":"Li, B., Peng, X., Wang, Z., Xu, J., Feng, D.: AOD-Net: all-in-one dehazing network. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 4770\u20134778 (2017). https:\/\/doi.org\/10.1109\/iccv.2017.511","DOI":"10.1109\/iccv.2017.511"},{"key":"3642_CR23","doi-asserted-by":"publisher","unstructured":"Ren, W., Liu, S., Zhang, H., Pan, J., Cao, X., Yang, M.-H.: Single image dehazing via multi-scale convolutional neural networks. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, 11\u201314 Oct, 2016, Proceedings, Part II 14, pp. 154\u2013169 (2016). Springer. https:\/\/doi.org\/10.1007\/978-3-319-46475-6_10","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"3642_CR24","doi-asserted-by":"publisher","unstructured":"Chen, D., He, M., Fan, Q., Liao, J., Zhang, L., Hou, D., Yuan, L., Hua, G.: Gated context aggregation network for image dehazing and deraining. In: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1375\u20131383 (2019). IEEE. https:\/\/doi.org\/10.1109\/wacv.2019.00151","DOI":"10.1109\/wacv.2019.00151"},{"key":"3642_CR25","doi-asserted-by":"publisher","unstructured":"Dong, H., Pan, J., Xiang, L., Hu, Z., Zhang, X., Wang, F., Yang, M.-H.: Multi-scale boosted dehazing network with dense feature fusion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2157\u20132167 (2020). https:\/\/doi.org\/10.1109\/cvpr42600.2020.00223","DOI":"10.1109\/cvpr42600.2020.00223"},{"key":"3642_CR26","doi-asserted-by":"publisher","unstructured":"Qin, X., Wang, Z., Bai, Y., Xie, X., Jia, H.: FFA-Net: feature fusion attention network for single image dehazing. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 11908\u201311915 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i07.6865","DOI":"10.1609\/aaai.v34i07.6865"},{"key":"3642_CR27","doi-asserted-by":"publisher","first-page":"1927","DOI":"10.1109\/tip.2023.3256763","volume":"32","author":"Y Song","year":"2023","unstructured":"Song, Y., He, Z., Qian, H., Du, X.: Vision transformers for single image dehazing. IEEE Trans. Image Process. 32, 1927\u20131941 (2023). https:\/\/doi.org\/10.1109\/tip.2023.3256763","journal-title":"IEEE Trans. Image Process."},{"key":"3642_CR28","doi-asserted-by":"publisher","unstructured":"Qiu, Y., Zhang, K., Wang, C., Luo, W., Li, H., Jin, Z.: MB-TaylorFormer: multi-branch efficient transformer expanded by taylor formula for image dehazing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 12802\u201312813 (2023). https:\/\/doi.org\/10.1109\/iccv51070.2023.01176","DOI":"10.1109\/iccv51070.2023.01176"},{"key":"3642_CR29","doi-asserted-by":"publisher","unstructured":"Zheng, Y., Zhan, J., He, S., Dong, J., Du, Y.: Curricular contrastive regularization for physics-aware single image dehazing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5785\u20135794 (2023). https:\/\/doi.org\/10.1109\/cvpr52729.2023.00560","DOI":"10.1109\/cvpr52729.2023.00560"},{"issue":"5","key":"3642_CR30","doi-asserted-by":"publisher","first-page":"1449","DOI":"10.1049\/ipr2.12726","volume":"17","author":"R Jiang","year":"2023","unstructured":"Jiang, R., Li, Y., Chen, C., Liu, W.: Two-stage learning framework for single image deraining. IET Image Proc. 17(5), 1449\u20131463 (2023). https:\/\/doi.org\/10.1049\/ipr2.12726","journal-title":"IET Image Proc."},{"issue":"9","key":"3642_CR31","doi-asserted-by":"publisher","first-page":"14101","DOI":"10.1007\/s11042-020-10428-0","volume":"80","author":"F Huo","year":"2021","unstructured":"Huo, F., Zhang, W., Wang, Q., Ren, W.: Two-stage image denoising algorithm based on noise localization. Multimed. Tools Appl. 80(9), 14101\u201314122 (2021). https:\/\/doi.org\/10.1007\/s11042-020-10428-0","journal-title":"Multimed. Tools Appl."},{"issue":"4","key":"3642_CR32","doi-asserted-by":"publisher","first-page":"8363","DOI":"10.1109\/lra.2020.3048667","volume":"6","author":"J Hu","year":"2021","unstructured":"Hu, J., Guo, X., Chen, J., Liang, G., Deng, F., Lam, T.L.: A two-stage unsupervised approach for low light image enhancement. IEEE Robot. Autom. Lett. 6(4), 8363\u20138370 (2021). https:\/\/doi.org\/10.1109\/lra.2020.3048667","journal-title":"IEEE Robot. Autom. Lett."},{"key":"3642_CR33","doi-asserted-by":"publisher","first-page":"76707","DOI":"10.1109\/access.2021.3082211","volume":"9","author":"Z Pan","year":"2021","unstructured":"Pan, Z., Lv, Q., Tan, Z.: A two-stage network for image deblurring. IEEE Access 9, 76707\u201376715 (2021). https:\/\/doi.org\/10.1109\/access.2021.3082211","journal-title":"IEEE Access"},{"key":"3642_CR34","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Tian, Y., Kong, Y., Zhong, B., Fu, Y.: Residual dense network for image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2472\u20132481 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00262","DOI":"10.1109\/CVPR.2018.00262"},{"key":"3642_CR35","doi-asserted-by":"publisher","unstructured":"Tan, R.T.: Visibility in bad weather from a single image. In: 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1\u20138 (2008). IEEE. https:\/\/doi.org\/10.1109\/cvpr.2008.4587643","DOI":"10.1109\/cvpr.2008.4587643"},{"issue":"11","key":"3642_CR36","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). https:\/\/doi.org\/10.1109\/tip.2015.2446191","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"3642_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1399504.1360671","volume":"27","author":"R Fattal","year":"2008","unstructured":"Fattal, R.: Single image dehazing. ACM Trans. Graph. TOG 27(3), 1\u20139 (2008). https:\/\/doi.org\/10.1145\/1399504.1360671","journal-title":"ACM Trans. Graph. TOG"},{"key":"3642_CR38","doi-asserted-by":"publisher","unstructured":"Berman, D., Avidan, S., et\u00a0al.: Non-local image dehazing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1674\u20131682 (2016). https:\/\/doi.org\/10.1109\/cvpr.2016.185","DOI":"10.1109\/cvpr.2016.185"},{"issue":"2","key":"3642_CR39","doi-asserted-by":"publisher","first-page":"999","DOI":"10.1109\/tip.2017.2771158","volume":"27","author":"TM Bui","year":"2017","unstructured":"Bui, T.M., Kim, W.: Single image dehazing using color ellipsoid prior. IEEE Trans. Image Process. 27(2), 999\u20131009 (2017). https:\/\/doi.org\/10.1109\/tip.2017.2771158","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"3642_CR40","doi-asserted-by":"publisher","first-page":"5279","DOI":"10.1007\/s00371-022-02659-z","volume":"39","author":"H Chen","year":"2023","unstructured":"Chen, H., Chen, R., Ma, L., Li, N.: Single-image dehazing via depth-guided deep retinex decomposition. Vis. Comput. 39(11), 5279\u20135291 (2023). https:\/\/doi.org\/10.1007\/s00371-022-02659-z","journal-title":"Vis. Comput."},{"key":"3642_CR41","doi-asserted-by":"publisher","first-page":"1217","DOI":"10.1109\/tip.2022.3140609","volume":"31","author":"H Bai","year":"2022","unstructured":"Bai, H., Pan, J., Xiang, X., Tang, J.: Self-guided image dehazing using progressive feature fusion. IEEE Trans. Image Process. 31, 1217\u20131229 (2022). https:\/\/doi.org\/10.1109\/tip.2022.3140609","journal-title":"IEEE Trans. Image Process."},{"key":"3642_CR42","doi-asserted-by":"publisher","first-page":"84699","DOI":"10.1109\/access.2023.3296592","volume":"11","author":"S Zhang","year":"2023","unstructured":"Zhang, S., Zhang, X., Shen, L.: Dual multi-scale dehazing network. IEEE Access 11, 84699\u201384708 (2023). https:\/\/doi.org\/10.1109\/access.2023.3296592","journal-title":"IEEE Access"},{"key":"3642_CR43","doi-asserted-by":"publisher","first-page":"6558","DOI":"10.1109\/tip.2023.3333564","volume":"32","author":"S Li","year":"2023","unstructured":"Li, S., Zhou, Y., Ren, W., Xiang, W.: PFONet: a progressive feedback optimization network for lightweight single image dehazing. IEEE Trans. Image Process. 32, 6558\u20136569 (2023). https:\/\/doi.org\/10.1109\/tip.2023.3333564","journal-title":"IEEE Trans. Image Process."},{"key":"3642_CR44","unstructured":"Howard, A.G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M., Adam, H.: MobileNets: efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017)"},{"key":"3642_CR45","doi-asserted-by":"publisher","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018). https:\/\/doi.org\/10.1109\/cvpr.2018.00745","DOI":"10.1109\/cvpr.2018.00745"},{"key":"3642_CR46","doi-asserted-by":"publisher","unstructured":"Wang, X., Girshick, R., Gupta, A., He, K.: Non-local neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7794\u20137803 (2018). https:\/\/doi.org\/10.1109\/cvpr.2018.00813","DOI":"10.1109\/cvpr.2018.00813"},{"key":"3642_CR47","unstructured":"Yu, F., Koltun, V.: Multi-scale context aggregation by dilated convolutions. arXiv preprint arXiv:1511.07122 (2015)"},{"key":"3642_CR48","doi-asserted-by":"publisher","unstructured":"Girshick, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448 (2015). https:\/\/doi.org\/10.1109\/iccv.2015.169","DOI":"10.1109\/iccv.2015.169"},{"key":"3642_CR49","doi-asserted-by":"publisher","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, 11\u201314 Oct, 2016, Proceedings, Part II 14, pp. 694\u2013711 (2016). Springer. https:\/\/doi.org\/10.1007\/978-3-319-46475-6_43","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"3642_CR50","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"3642_CR51","doi-asserted-by":"publisher","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 248\u2013255 (2009). IEEE. https:\/\/doi.org\/10.1109\/cvpr.2009.5206848","DOI":"10.1109\/cvpr.2009.5206848"},{"key":"3642_CR52","doi-asserted-by":"publisher","unstructured":"Valanarasu, J.M.J., Yasarla, R., Patel, V.M.: TransWeather: transformer-based restoration of images degraded by adverse weather conditions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2353\u20132363 (2022). https:\/\/doi.org\/10.1109\/cvpr52688.2022.00239","DOI":"10.1109\/cvpr52688.2022.00239"},{"issue":"1","key":"3642_CR53","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1109\/TIP.2018.2867951","volume":"28","author":"B Li","year":"2018","unstructured":"Li, B., Ren, W., Fu, D., Tao, D., Feng, D., Zeng, W., Wang, Z.: Benchmarking single-image dehazing and beyond. IEEE Trans. Image Process. 28(1), 492\u2013505 (2018). https:\/\/doi.org\/10.1109\/TIP.2018.2867951","journal-title":"IEEE Trans. Image Process."},{"key":"3642_CR54","doi-asserted-by":"publisher","unstructured":"Ancuti, C.O., Ancuti, C., Timofte, R., De\u00a0Vleeschouwer, C.: O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 754\u2013762 (2018). https:\/\/doi.org\/10.1109\/cvprw.2018.00119","DOI":"10.1109\/cvprw.2018.00119"},{"key":"3642_CR55","doi-asserted-by":"publisher","unstructured":"Ancuti, C.O., Ancuti, C., Timofte, R.: NH-HAZE: an image dehazing benchmark with non-homogeneous hazy and haze-free images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 444\u2013445 (2020). https:\/\/doi.org\/10.1109\/cvprw50498.2020.00230","DOI":"10.1109\/cvprw50498.2020.00230"},{"key":"3642_CR56","doi-asserted-by":"publisher","unstructured":"Ancuti, C.O., Ancuti, C., Sbert, M., Timofte, R.: Dense-Haze: a benchmark for image dehazing with dense-haze and haze-free images. In: 2019 IEEE International Conference on Image Processing (ICIP), pp. 1014\u20131018 (2019). IEEE. https:\/\/doi.org\/10.1109\/icip.2019.8803046","DOI":"10.1109\/icip.2019.8803046"},{"issue":"13","key":"3642_CR57","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). https:\/\/doi.org\/10.1049\/el:20080522","journal-title":"Electron. Lett."},{"issue":"4","key":"3642_CR58","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). https:\/\/doi.org\/10.1109\/tip.2003.819861","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"3642_CR59","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1002\/col.20070","volume":"30","author":"G Sharma","year":"2005","unstructured":"Sharma, G., Wu, W., Dalal, E.N.: The CIEDE2000 color-difference formula: implementation notes, supplementary test data, and mathematical observations. Color Res. Appl. 30(1), 21\u201330 (2005). https:\/\/doi.org\/10.1002\/col.20070","journal-title":"Color Res. Appl."},{"issue":"3","key":"3642_CR60","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2012","unstructured":"Mittal, A., Soundararajan, R., Bovik, A.C.: Making a \u201ccompletely blind\u2019\u2019 image quality analyzer. IEEE Signal Process. Lett. 20(3), 209\u2013212 (2012). https:\/\/doi.org\/10.1109\/LSP.2012.2227726","journal-title":"IEEE Signal Process. Lett."},{"issue":"11","key":"3642_CR61","doi-asserted-by":"publisher","first-page":"3888","DOI":"10.1109\/TIP.2015.2456502","volume":"24","author":"LK Choi","year":"2015","unstructured":"Choi, L.K., You, J., Bovik, A.C.: Referenceless prediction of perceptual fog density and perceptual image defogging. IEEE Trans. Image Process. 24(11), 3888\u20133901 (2015). https:\/\/doi.org\/10.1109\/TIP.2015.2456502","journal-title":"IEEE Trans. Image Process."}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03642-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03642-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03642-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T10:23:41Z","timestamp":1744799021000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03642-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,18]]},"references-count":61,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["3642"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03642-6","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2024,10,18]]},"assertion":[{"value":"3 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 October 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}