{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T01:56:39Z","timestamp":1775181399148,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T00:00:00Z","timestamp":1752451200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T00:00:00Z","timestamp":1752451200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"crossref","award":["CSTB2022NSCQ-MSX1632"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX1632"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"crossref","award":["CSTB2022NSCQ-MSX1632"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX1632"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"crossref","award":["CSTB2022NSCQ-MSX1632"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX1632"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s11760-025-04515-8","type":"journal-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T17:35:59Z","timestamp":1752514559000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["DehazeDiff: Image Dehazing via Mask-guided Diffusion Model"],"prefix":"10.1007","volume":"19","author":[{"given":"Liqun","family":"Luo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yizhou","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ju","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,14]]},"reference":[{"issue":"3","key":"4515_CR1","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1016\/0034-4257(88)90019-3","volume":"24","author":"PS Chavez Jr","year":"1988","unstructured":"Chavez, P.S., Jr.: An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sens. Environ. 24(3), 459\u2013479 (1988)","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"4515_CR2","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)","journal-title":"IEEE Trans. Image Process."},{"key":"4515_CR3","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: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14, pp. 154\u2013169 (2016). Springer","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"4515_CR4","doi-asserted-by":"crossref","unstructured":"Parihar, A.S., Gupta, Y.K., Singodia, Y., Singh, V., Singh, K.: A comparative study of image dehazing algorithms. In: 2020 5th International Conference on Communication and Electronics Systems (ICCES), pp. 766\u2013771 (2020). IEEE","DOI":"10.1109\/ICCES48766.2020.9138037"},{"key":"4515_CR5","doi-asserted-by":"crossref","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)","DOI":"10.1109\/CVPR52729.2023.00560"},{"key":"4515_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2024.102277","volume":"106","author":"Z Lihe","year":"2024","unstructured":"Lihe, Z., He, J., Yuan, Q., Jin, X., Xiao, Y., Zhang, L.: Phdnet: A novel physic-aware dehazing network for remote sensing images. Information Fusion 106, 102277 (2024)","journal-title":"Information Fusion"},{"key":"4515_CR7","doi-asserted-by":"crossref","unstructured":"Wen, Y., Gao, T., Zhang, J., Li, Z., Chen, T.: Encoder-free multi-axis physics-aware fusion network for remote sensing image dehazing. IEEE Transactions on Geoscience and Remote Sensing (2023)","DOI":"10.1109\/TGRS.2023.3325927"},{"issue":"5","key":"4515_CR8","doi-asserted-by":"publisher","first-page":"1557","DOI":"10.1007\/s11263-023-01940-5","volume":"132","author":"Y Yang","year":"2024","unstructured":"Yang, Y., Wang, C., Guo, X., Tao, D.: Robust unpaired image dehazing via density and depth decomposition. Int. J. Comput. Vision 132(5), 1557\u20131577 (2024)","journal-title":"Int. J. Comput. Vision"},{"key":"4515_CR9","doi-asserted-by":"crossref","unstructured":"Shen, H., Zhao, Z.-Q., Zhang, Y., Zhang, Z.: Mutual information-driven triple interaction network for efficient image dehazing. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 7\u201316 (2023)","DOI":"10.1145\/3581783.3612299"},{"key":"4515_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2020.103014","volume":"74","author":"B Chaitanya","year":"2021","unstructured":"Chaitanya, B., Mukherjee, S.: Single image dehazing using improved cyclegan. J. Vis. Commun. Image Represent. 74, 103014 (2021)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"6","key":"4515_CR11","doi-asserted-by":"publisher","first-page":"2511","DOI":"10.1007\/s11554-021-01143-6","volume":"18","author":"G Yang","year":"2021","unstructured":"Yang, G., Evans, A.N.: Improved single image dehazing methods for resource-constrained platforms. J. Real-Time Image Proc. 18(6), 2511\u20132525 (2021)","journal-title":"J. Real-Time Image Proc."},{"key":"4515_CR12","doi-asserted-by":"crossref","unstructured":"Yang, Y., Zou, D., Song, X., Zhang, X.: Dehazedm: Image dehazing via patch autoencoder based on diffusion models. In: 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 3783\u20133788 (2023). IEEE","DOI":"10.1109\/SMC53992.2023.10394653"},{"key":"4515_CR13","unstructured":"Zhou, M., Huang, J., Guo, C.-L., Li, C.: Fourmer: An efficient global modeling paradigm for image restoration. In: International Conference on Machine Learning, pp. 42589\u201342601 (2023). PMLR"},{"key":"4515_CR14","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)","journal-title":"IEEE Trans. Image Process."},{"key":"4515_CR15","unstructured":"Lim, J., Chang, H.J., Choi, J.Y.: Pmnet: Learning of disentangled pose and movement for unsupervised motion retargeting. In: BMVC, vol. 2, p. 7 (2019)"},{"key":"4515_CR16","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Adv. Neural. Inf. Process. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4515_CR17","unstructured":"Welling, M., Teh, Y.W.: Bayesian learning via stochastic gradient langevin dynamics. In: Proceedings of the 28th International Conference on Machine Learning (ICML-11), pp. 681\u2013688 (2011). Citeseer"},{"key":"4515_CR18","doi-asserted-by":"crossref","unstructured":"Dong, Y., Liu, Y., Zhang, H., Chen, S., Qiao, Y.: Fd-gan: Generative adversarial networks with fusion-discriminator for single image dehazing. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, pp. 10729\u201310736 (2020)","DOI":"10.1609\/aaai.v34i07.6701"},{"issue":"10","key":"4515_CR19","doi-asserted-by":"publisher","first-page":"7119","DOI":"10.1007\/s11760-024-03373-0","volume":"18","author":"X Gong","year":"2024","unstructured":"Gong, X., Zheng, Z., Du, H.: Tsnet: a two-stage network for image dehazing with multi-scale fusion and adaptive learning. SIViP 18(10), 7119\u20137130 (2024)","journal-title":"SIViP"},{"issue":"3","key":"4515_CR20","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1109\/83.908502","volume":"10","author":"SS Agaian","year":"2001","unstructured":"Agaian, S.S., Panetta, K., Grigoryan, A.M.: Transform-based image enhancement algorithms with performance measure. IEEE Trans. Image Process. 10(3), 367\u2013382 (2001)","journal-title":"IEEE Trans. Image Process."},{"key":"4515_CR21","doi-asserted-by":"publisher","first-page":"2692","DOI":"10.1109\/TIP.2019.2952032","volume":"29","author":"A Golts","year":"2019","unstructured":"Golts, A., Freedman, D., Elad, M.: Unsupervised single image dehazing using dark channel prior loss. IEEE Trans. Image Process. 29, 2692\u20132701 (2019)","journal-title":"IEEE Trans. Image Process."},{"issue":"18","key":"4515_CR22","doi-asserted-by":"publisher","first-page":"10475","DOI":"10.3390\/app131810475","volume":"13","author":"H Suo","year":"2023","unstructured":"Suo, H., Guan, J., Ma, M., Huo, Y., Cheng, Y., Wei, N., Zhang, L.: Dynamic dark channel prior dehazing with polarization. Appl. Sci. 13(18), 10475 (2023)","journal-title":"Appl. Sci."},{"key":"4515_CR23","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.patcog.2017.10.013","volume":"77","author":"J Gu","year":"2018","unstructured":"Gu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., et al.: Recent advances in convolutional neural networks. Pattern Recogn. 77, 354\u2013377 (2018)","journal-title":"Pattern Recogn."},{"key":"4515_CR24","doi-asserted-by":"crossref","unstructured":"Cui, Y., Tao, Y., Bing, Z., Ren, W., Gao, X., Cao, X., Huang, K., Knoll, A.: Selective frequency network for image restoration. In: The Eleventh International Conference on Learning Representations (2023)","DOI":"10.1109\/ICCV51070.2023.01195"},{"key":"4515_CR25","doi-asserted-by":"crossref","unstructured":"Cui, Y., Ren, W., Cao, X., Knoll, A.: Image restoration via frequency selection. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023)","DOI":"10.1109\/TPAMI.2023.3330416"},{"key":"4515_CR26","doi-asserted-by":"crossref","unstructured":"Cui, Y., Ren, W., Cao, X., Knoll, A.: Focal network for image restoration. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 13001\u201313011 (2023)","DOI":"10.1109\/ICCV51070.2023.01195"},{"key":"4515_CR27","doi-asserted-by":"crossref","unstructured":"Cui, Y., Ren, W., Knoll, A.: Omni-kernel network for image restoration. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, pp. 1426\u20131434 (2024)","DOI":"10.1609\/aaai.v38i2.27907"},{"key":"4515_CR28","volume":"102","author":"S Kan","year":"2022","unstructured":"Kan, S., Zhang, Y., Zhang, F., Cen, Y.: A gan-based input-size flexibility model for single image dehazing. Signal Processing: Image Communication 102, 116599 (2022)","journal-title":"Signal Processing: Image Communication"},{"key":"4515_CR29","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)"},{"key":"4515_CR30","doi-asserted-by":"crossref","unstructured":"Cheng, L., Ba, X., Qu, Y.: Dehazediff: When conditional guidance meets diffusion models for image dehazing. In: 2024 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1\u20135 (2024). IEEE","DOI":"10.1109\/ISCAS58744.2024.10558580"},{"key":"4515_CR31","unstructured":"Yu, H., Huang, J., Zheng, K., Zhao, F.: High-quality image dehazing with diffusion model. arXiv preprint arXiv:2308.11949 (2023)"},{"key":"4515_CR32","doi-asserted-by":"crossref","unstructured":"Xiong, J., Yan, X., Wang, Y., Zhao, W., Zhang, X.-P., Wei, M.: Rshazediff: A unified fourier-aware diffusion model for remote sensing image dehazing. arXiv preprint arXiv:2405.09083 (2024)","DOI":"10.1109\/TITS.2024.3487972"},{"issue":"3","key":"4515_CR33","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/0370-1573(76)90029-6","volume":"24","author":"NG Van Kampen","year":"1976","unstructured":"Van Kampen, N.G.: Stochastic differential equations. Phys. Rep. 24(3), 171\u2013228 (1976)","journal-title":"Phys. Rep."},{"key":"4515_CR34","doi-asserted-by":"crossref","unstructured":"Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I., Irani, M.: Imagic: Text-based real image editing with diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6007\u20136017 (2023)","DOI":"10.1109\/CVPR52729.2023.00582"},{"key":"4515_CR35","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"4515_CR36","doi-asserted-by":"crossref","unstructured":"Peebles, W., Xie, S.: Scalable diffusion models with transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4195\u20134205 (2023)","DOI":"10.1109\/ICCV51070.2023.00387"},{"key":"4515_CR37","doi-asserted-by":"crossref","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)","DOI":"10.1109\/CVPRW50498.2020.00230"},{"key":"4515_CR38","doi-asserted-by":"crossref","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","DOI":"10.1109\/ICIP.2019.8803046"},{"key":"4515_CR39","doi-asserted-by":"crossref","unstructured":"Nabila, P., Setiawan, E.B.: Adam and adamw optimization algorithm application on bert model for hate speech detection on twitter. In: 2024 International Conference on Data Science and Its Applications (ICoDSA), pp. 346\u2013351 (2024). IEEE","DOI":"10.1109\/ICoDSA62899.2024.10651619"},{"key":"4515_CR40","doi-asserted-by":"crossref","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)","DOI":"10.1109\/ICCV.2019.00741"},{"key":"4515_CR41","doi-asserted-by":"crossref","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)","DOI":"10.1609\/aaai.v34i07.6865"},{"key":"4515_CR42","doi-asserted-by":"crossref","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)","DOI":"10.1109\/CVPR42600.2020.00223"},{"key":"4515_CR43","doi-asserted-by":"crossref","unstructured":"Wu, H., Qu, Y., Lin, S., Zhou, J., Qiao, R., Zhang, Z., Xie, Y., Ma, L.: Contrastive learning for compact single image dehazing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10551\u201310560 (2021)","DOI":"10.1109\/CVPR46437.2021.01041"},{"issue":"1","key":"4515_CR44","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/TPAMI.2022.3152247","volume":"45","author":"K Han","year":"2022","unstructured":"Han, K., Wang, Y., Chen, H., Chen, X., Guo, J., Liu, Z., Tang, Y., Xiao, A., Xu, C., Xu, Y., et al.: A survey on vision transformer. IEEE Trans. Pattern Anal. Mach. Intell. 45(1), 87\u2013110 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04515-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04515-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04515-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,7]],"date-time":"2025-09-07T09:25:50Z","timestamp":1757237150000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04515-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,14]]},"references-count":44,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["4515"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04515-8","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,14]]},"assertion":[{"value":"16 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 July 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 July 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and\/or discussion reported in this paper. The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"874"}}