{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T17:21:13Z","timestamp":1783185673612,"version":"3.54.6"},"reference-count":29,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2024,10,1]]},"DOI":"10.1587\/transinf.2024edl8008","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T22:12:57Z","timestamp":1727734377000},"page":"1380-1384","source":"Crossref","is-referenced-by-count":1,"title":["IAD-Net: Single-Image Dehazing Network Based on Image Attention"],"prefix":"10.1587","volume":"E107.D","author":[{"given":"Zheqing","family":"ZHANG","sequence":"first","affiliation":[{"name":"School of Big Data and Artificial Intelligence, Chizhou University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hao","family":"ZHOU","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuan","family":"LI","sequence":"additional","affiliation":[{"name":"College of Computer and Information Science, Southwest University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"JIANG","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] W. Kim, J. You, and J. Jeong, \u201cContrast enhancement using histogram equalization based on logarithmic mapping,\u201d Optical Engineering, vol.51, no.6, 067002, 2012. 10.1117\/1.oe.51.6.067002","DOI":"10.1117\/1.OE.51.6.067002"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] H. Li, W.H. Xie, X.G. Wang, S.S. Liu, Y.Y. Gai, and L. Yang, \u201cGpu implementation of multi-scale retinex image enhancement algorithm,\u201d 2016 IEEE\/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp.1-5, 2016. 10.1109\/aiccsa.2016.7945715","DOI":"10.1109\/AICCSA.2016.7945715"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] K.M. He, J. Sun, and X.O. 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":"4","doi-asserted-by":"publisher","unstructured":"[4] Z. Wei, G. Zhu, X. Liang, W. Liu, \u201cAn image fusion dehazing algorithm based on dark channel prior and retinex,\u201d International Journal of Computational Science and Engineering, vol.23, no.2, pp.115-123, 2020. 10.1504\/ijcse.2020.110556","DOI":"10.1504\/IJCSE.2020.110556"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] X.P. Yuan, Y.Y. Chen, and H. Shi, \u201cImproved image dehazing algorithm based on haze-line and dark channel prior,\u201d Laser & Optoelectronics Progress, vol.59, no.8, 0810014, 2022.","DOI":"10.3788\/LOP202259.0810014"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] Y. Wang, T.-Z. Huang, X.-L. Zhao, L.-J. Deng, and T.-Y. Ji, \u201cA convex single image dehazing model via sparse dark channel prior,\u201d Applied Mathematics and Computation, vol.375, 125085, 2020. 10.1016\/j.amc.2020.125085","DOI":"10.1016\/j.amc.2020.125085"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] Z. Lu, B. Long, and S. Yang, \u201cSaturation Based Iterative Approach for Single Image Dehazing,\u201d IEEE Signal Process. Lett., vol.27, pp.665-669, 2020. 10.1109\/lsp.2020.2985570","DOI":"10.1109\/LSP.2020.2985570"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] Y. Liu, Z.S. Yan, J.G. Tan, and Y.C. Li, \u201cMulti-Purpose Oriented Single Nighttime Image Haze Removal Based on Unified Variational Retinex Model,\u201d IEEE Trans. Circuits Syst. Video Technol., vol.33, no.4, pp.1643-1657, 2023. 10.1109\/tcsvt.2022.3214430","DOI":"10.1109\/TCSVT.2022.3214430"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] B. Cai, X.M. Xu, K. Jia, C.M. Qing, and D.C. 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":"10","doi-asserted-by":"crossref","unstructured":"[10] B. Li, X. Peng, Z.Y. Wang, D. Xu, and J.Z. Feng, \u201cAod-net: All-in-one dehazing network,\u201d Proc. IEEE International Conference on Computer Vision, pp.4780-4788, 2017.","DOI":"10.1109\/ICCV.2017.511"},{"key":"11","doi-asserted-by":"crossref","unstructured":"[11] W. Ren, L. Ma, J. Zhang, J. Pan, X. Cao, W. Liu, and M.H. Yang, \u201cGated fusion network for single image dehazing,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.3253-3261, 2018.","DOI":"10.1109\/CVPR.2018.00343"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] D. Chen, M. He, Q. Fan, J. Liao, L. Zhang, D. Hou, L. Yuan, and G. Hua, \u201cGated context aggregation network for image dehazing and deraining,\u201d Proc. 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pp.1375-1383, 2019.","DOI":"10.1109\/WACV.2019.00151"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[14] W. Ren, S. Liu, H. Zhang, J. Pan, X. Cao, and M.H. Yang, \u201cSingle image dehazing via multi-scale convolutional neural networks,\u201d Proc. European Conference on Computer Vision, pp.154-169, Springer, 2016.","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"14","unstructured":"[15] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, L. Kaiser, and I. Polosukhin, \u201cAttention is all you need,\u201d Advances in Neural Information Processing Systems, vol.30, 2017."},{"key":"15","unstructured":"[16] D. Zhao, J. Li, H. Li, and L. Xu, \u201cHybrid local-global transformer for image dehazing,\u201d arXiv preprint arXiv:2109.07100, 2021."},{"key":"16","doi-asserted-by":"crossref","unstructured":"[17] J.M.J. Valanarasu, R. Yasarla, and V.M. Patel, \u201cTransweather: Transformer-based restoration of images degraded by adverse weather conditions,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.2353-2363, 2022.","DOI":"10.1109\/CVPR52688.2022.00239"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[18] C.L. Guo, Q.X. Yan, S. Anwar, R.M. Cong, W.Q. Ren, and C.Y. Li, \u201cImage dehazing transformer with transmission-aware 3D position embedding,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.5812-5820, 2022.","DOI":"10.1109\/CVPR52688.2022.00572"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[19] Y.D. Song, Z.Q. He, H. Qian, and X. Du, \u201cVision transformers for single image dehazing,\u201d IEEE Trans. Image Process., vol.32, pp.1927-1941, 2023. 10.1109\/tip.2023.3256763","DOI":"10.1109\/TIP.2023.3256763"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[20] H. Zhou, Z.K. Chen, Y. Liu, Y.P. Sheng, W.Q. Ren, and H.L. Xiong, \u201cPhysical-priors-guided DehazeFormer,\u201d Knowledge-Based Systems, vol.266, 110410, 2023. 10.1016\/j.knosys.2023.110410","DOI":"10.1016\/j.knosys.2023.110410"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[21] Y. Liu, Z.S. Yan, S.X. Chen, T. Ye, W.Q. Ren, E, Chen, J.G. Tan, and Y.C. Li, \u201cNighthazeformer: Single nighttime haze removal using prior query transformer,\u201d Proc. 31st ACM International Conference on Multimedia, pp.4119-4128, 2023. 10.1145\/3581783.3611744","DOI":"10.1145\/3581783.3611744"},{"key":"21","doi-asserted-by":"publisher","unstructured":"[22] S.W. Zhang and C.L. Zhang, \u201cModified U-Net for plant diseased leaf image segmentation,\u201d Computers and Electronics in Agriculture, vol.204, 107511, 2023. 10.1016\/j.compag.2022.107511","DOI":"10.1016\/j.compag.2022.107511"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[23] C.O. Ancuti, C. Ancuti, R. Timofte, and C.D. Vleeschouwer, \u201cO-haze: A dehazing benchmark with real hazy and haze-free outdoor images,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.754-762, 2018.","DOI":"10.1109\/CVPRW.2018.00119"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[24] C.O. Ancuti, C. Ancuti, and R. Timofte, \u201cNH-HAZE: An image dehazing benchmark with non-homogeneous hazy and haze-free images,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.444-445, 2020.","DOI":"10.1109\/CVPRW50498.2020.00230"},{"key":"24","doi-asserted-by":"crossref","unstructured":"[25] X.H. Liu, Y.R. Ma, Z.H. Shi, and J. Chen, \u201cGriddehazenet: Attention-based multi-scale network for image dehazing,\u201d Proc. IEEE\/CVF International Conference on Computer Vision, pp.7314-7323, 2019.","DOI":"10.1109\/ICCV.2019.00741"},{"key":"25","doi-asserted-by":"publisher","unstructured":"[26] X. Qin, Z. Wang, Y. Bai, X. Xie, and H. Jia, \u201cFFA-Net: Feature fusion attention network for single image dehazing,\u201d Proc. AAAI Conference on Artificial Intelligence, vol.34, no.7, pp.11908-11915, 2020. 10.1609\/aaai.v34i07.6865","DOI":"10.1609\/aaai.v34i07.6865"},{"key":"26","doi-asserted-by":"publisher","unstructured":"[27] S. Zhao, L. Zhang, Y. Shen, and Y. Zhou, \u201cRefineDNet: A weakly supervised refinement framework for single image dehazing,\u201d IEEE Trans. Image Process., vol.30, pp.3391-3404, 2021. 10.1109\/tip.2021.3060873","DOI":"10.1109\/TIP.2021.3060873"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[28] Z. Chen, Y. Wang, Y. Yang, and D. Liu, \u201cPSD: Principled synthetic-to-real dehazing guided by physical priors,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.7180-7189, 2021.","DOI":"10.1109\/CVPR46437.2021.00710"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[29] Y. Yang, C. Wang, R. Liu, L. Zhang, X. Guo, and D. Tao, \u201cSelf-augmented unpaired image dehazing via density and depth decomposition,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.2037-2046, 2022.","DOI":"10.1109\/CVPR52688.2022.00208"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[30] B.Y. Li, W.Q. Ren, D.P. Fu, D.C. Tao, D. Feng, W.J. Zeng, and Z.Y. Wang, \u201cReside: A benchmark for single image dehazing,\u201d IEEE Trans. Image Process., vol.28, no.1, pp.492-505, 2019. 10.1109\/tip.2018.2867951","DOI":"10.1109\/TIP.2018.2867951"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E107.D\/10\/E107.D_2024EDL8008\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,5]],"date-time":"2024-10-05T03:45:29Z","timestamp":1728099929000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E107.D\/10\/E107.D_2024EDL8008\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,1]]},"references-count":29,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2024edl8008","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,1]]},"article-number":"2024EDL8008"}}