基于雾气浓度估计的图像去雾算法
根据雾气浓度的视觉特征,提出一种雾气浓度估计模型.在此基础上,结合大气散射模型,提出一种新的图像去雾算法.首先,基于雾气浓度估计模型计算出雾气浓度量化图,利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光;然后,对量化图中的“非雾气最浓”区域再次进行聚类处理,根据文中所提最优透射率评价指标估计出每个聚类单元的透射率,将全球光与透射图以及有雾图像导入散射模型,便可达到去雾的目的;最后,针对去雾后图像较实际场景偏暗,提出一种基于小波域的多尺度锐化算法进行增强处理,以改善其主观视觉质量.实验结果表明,本文算法与现有主流算法相比,具有更好的去雾效果,并且其计算速度也相对较快....
Saved in:
| Published in | 自动化学报 Vol. 42; no. 9; pp. 1367 - 1379 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
南京邮电大学物联网学院 南京 210003
2016
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0254-4156 1874-1029 |
| DOI | 10.16383/j.aas.2016.c150525 |
Cover
Loading…
| Abstract | 根据雾气浓度的视觉特征,提出一种雾气浓度估计模型.在此基础上,结合大气散射模型,提出一种新的图像去雾算法.首先,基于雾气浓度估计模型计算出雾气浓度量化图,利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光;然后,对量化图中的“非雾气最浓”区域再次进行聚类处理,根据文中所提最优透射率评价指标估计出每个聚类单元的透射率,将全球光与透射图以及有雾图像导入散射模型,便可达到去雾的目的;最后,针对去雾后图像较实际场景偏暗,提出一种基于小波域的多尺度锐化算法进行增强处理,以改善其主观视觉质量.实验结果表明,本文算法与现有主流算法相比,具有更好的去雾效果,并且其计算速度也相对较快. |
|---|---|
| AbstractList | 根据雾气浓度的视觉特征,提出一种雾气浓度估计模型.在此基础上,结合大气散射模型,提出一种新的图像去雾算法.首先,基于雾气浓度估计模型计算出雾气浓度量化图,利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光;然后,对量化图中的“非雾气最浓”区域再次进行聚类处理,根据文中所提最优透射率评价指标估计出每个聚类单元的透射率,将全球光与透射图以及有雾图像导入散射模型,便可达到去雾的目的;最后,针对去雾后图像较实际场景偏暗,提出一种基于小波域的多尺度锐化算法进行增强处理,以改善其主观视觉质量.实验结果表明,本文算法与现有主流算法相比,具有更好的去雾效果,并且其计算速度也相对较快. 根据雾气浓度的视觉特征，提出一种雾气浓度估计模型。在此基础上，结合大气散射模型，提出一种新的图像去雾算法。首先，基于雾气浓度估计模型计算出雾气浓度量化图，利用模糊聚类算法在量化图中识别出雾气最浓区域并估计出全球光；然后，对量化图中的“非雾气最浓”区域再次进行聚类处理，根据文中所提最优透射率评价指标估计出每个聚类单元的透射率，将全球光与透射图以及有雾图像导入散射模型，便可达到去雾的目的；最后，针对去雾后图像较实际场景偏暗，提出一种基于小波域的多尺度锐化算法进行增强处理，以改善其主观视觉质量。实验结果表明，本文算法与现有主流算法相比，具有更好的去雾效果，并且其计算速度也相对较快。 |
| Abstract_FL | This paper proposes a haze thickness estimation model based on visual characteristics of haze thickness, and combines this model with atmosphere scattering model to present an innovative image dehazing algorithm. First, a haze thickness quantitative map is calculated via the haze thickness estimation model, from which the thickest area is identified by the fuzzy clustering algorithm and global atmospheric light is estimated. After that, the algorithm carries on clustering processing towards the non-thickest area in the quantitative map, and estimates the transmission of each cluster unit according to the optimized transmission evaluation index mentioned in this paper. The haze-free image can be restored from scattering model with global light, refined transmission map and original hazy image. At last, we propose a multi-scale sharpening algorithm based on wavelet domain to make up for the defect that the haze-free image is dark-look so as to improve the visual effect. Several numerical experiments demonstrate that the proposed method outperforms the mainstream dehazing algorithms in daze removal effect at a much lower implementation cost. |
| Author | 鞠铭烨 张登银 纪应天 |
| AuthorAffiliation | 南京邮电大学物联网学院,南京210003 |
| AuthorAffiliation_xml | – name: 南京邮电大学物联网学院 南京 210003 |
| Author_FL | JU Ming-Ye JI Ying-Tian ZHANG Deng-Yin |
| Author_FL_xml | – sequence: 1 fullname: JU Ming-Ye – sequence: 2 fullname: ZHANG Deng-Yin – sequence: 3 fullname: JI Ying-Tian |
| Author_xml | – sequence: 1 fullname: 鞠铭烨 张登银 纪应天 |
| BookMark | eNotj7tKA0EYhQeJ4BrzBHYWdrv-M7P_XEoJ3iBgof0ye5lc0I3uIl5arZNCRTCF2FiGgNhEydNkE30LV2J1ivPxHc4qqaTdNCFknYJHBVd8q-MZk3sMqPAiioAMl4hDlfRdCkxXiAMMfdenKFZILc_bIVDpS804OMQtXsbTce9nMJmNHmYf98X4bfo1-h6-zp_visGkuO0Xvc-ynQ-fZu-Pa2TZmpM8qf1nlRzt7hzX993G4d5BfbvhRqiUy6hWcax4ElolEsVAAoaaCR4hM-hrnnATWxEaiKyWCnmCVPmhlBItjWNeJZsL66VJrUmbQad7kaXlXnATt67Cv6OgAVQJbizAqNVNm-ftEj3L2qcmuw6E0BqoQsl_AYqlY4c |
| ContentType | Journal Article |
| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| Copyright_xml | – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
| DBID | 2RA 92L CQIGP W92 ~WA 2B. 4A8 92I 93N PSX TCJ |
| DOI | 10.16383/j.aas.2016.c150525 |
| DatabaseName | 维普_期刊 中文科技期刊数据库-CALIS站点 维普中文期刊数据库 中文科技期刊数据库-工程技术 中文科技期刊数据库- 镜像站点 Wanfang Data Journals - Hong Kong WANFANG Data Centre Wanfang Data Journals 万方数据期刊 - 香港版 China Online Journals (COJ) China Online Journals (COJ) |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| DocumentTitleAlternate | Image Haze Removal Algorithm Based on Haze Thickness Estimation |
| DocumentTitle_FL | Image Haze Removal Algorithm Based on Haze Thickness Estimation |
| EISSN | 1874-1029 |
| EndPage | 1379 |
| ExternalDocumentID | zdhxb201609008 669901857 |
| GrantInformation_xml | – fundername: 国家自然科学基金; 江苏省高校自然科学研究重大项目; 江苏省产学研前瞻性联合研究项目(BY2014014)资助Supported by National Natural Science Foundation of China; Key University Science Research Project of Jiangsu Province; Prospective Joint Research Project of Jiangsu Province funderid: (61571241); (15KJA510002); (61571241); (15KJA510002); (BY2014014) |
| GroupedDBID | --K -0Y .~1 0R~ 1B1 1~. 1~5 2B. 2C0 2RA 4.4 457 4G. 5GY 5VS 5XA 5XJ 7-5 71M 8P~ 92H 92I 92L AAIKJ AALRI AAQFI AAXUO ACGFS ADEZE ADTZH AECPX AEKER AFTJW AGHFR AGYEJ AITUG AJOXV ALMA_UNASSIGNED_HOLDINGS BLXMC CCEZO CQIGP CS3 CUBFJ CW9 EBS EFLBG EJD EO8 EO9 EP2 EP3 FDB FEDTE FNPLU GBLVA HVGLF HZ~ IHE J1W JJJVA M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 ROL RPZ SDF SDG SES TCJ TGT U1G U5S W92 ~WA 4A8 93N ABJNI ABWVN ACRPL ADNMO PSX |
| ID | FETCH-LOGICAL-c588-2198dd83ebf86e820705b9263c52a5493e3adf6ba0cf97853e5184b7775f1dd3 |
| ISSN | 0254-4156 |
| IngestDate | Thu May 29 04:10:30 EDT 2025 Wed Feb 14 10:15:46 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Keywords | 图像去雾 atmosphere scattering model 大气散射模型 haze thickness estimation model fuzzy clustering 模糊聚类 雾气浓度估计模型 Image daze removal 导向滤波器 guided filter |
| Language | Chinese |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c588-2198dd83ebf86e820705b9263c52a5493e3adf6ba0cf97853e5184b7775f1dd3 |
| Notes | Image daze removal, fuzzy clustering, haze thickness estimation model, guided filter, atmosphere scattering model This paper proposes a haze thickness estimation model based on visual characteristics of haze thickness, and combines this model with atmosphere scattering model to present an innovative image dehazing algorithm. First, a haze thickness quantitative map is calculated via the haze thickness estimation model, from which the thickest area is identified by the fuzzy clustering algorithm and global atmospheric light is estimated. After that, the algorithm carries on clustering processing towards the non-thickest area in the quantitative map, and estimates the transmission of each cluster unit according to the optimized transmission evaluation index mentioned in this paper. The haze-free image can be restored from scattering model with global light, refined transmission map and original hazy image. At last, we propose a multi- scale sharpening algorithm based on wavelet domain to make up for the defect t |
| PageCount | 13 |
| ParticipantIDs | wanfang_journals_zdhxb201609008 chongqing_primary_669901857 |
| PublicationCentury | 2000 |
| PublicationDate | 2016 |
| PublicationDateYYYYMMDD | 2016-01-01 |
| PublicationDate_xml | – year: 2016 text: 2016 |
| PublicationDecade | 2010 |
| PublicationTitle | 自动化学报 |
| PublicationTitleAlternate | Acta Automatica Sinica |
| PublicationTitle_FL | Acta Automatica Sinica |
| PublicationYear | 2016 |
| Publisher | 南京邮电大学物联网学院 南京 210003 |
| Publisher_xml | – name: 南京邮电大学物联网学院 南京 210003 |
| SSID | ssib017479230 ssib001102911 ssib006576350 ssib051375349 ssib007293330 ssj0059721 ssib007290157 ssib023646446 ssib005904210 |
| Score | 2.1245162 |
| Snippet | ... |
| SourceID | wanfang chongqing |
| SourceType | Aggregation Database Publisher |
| StartPage | 1367 |
| SubjectTerms | 图像去雾 大气散射模型 导向滤波器 模糊聚类 雾气浓度估计模型 |
| Title | 基于雾气浓度估计的图像去雾算法 |
| URI | http://lib.cqvip.com/qk/90250X/201609/669901857.html https://d.wanfangdata.com.cn/periodical/zdhxb201609008 |
| Volume | 42 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR27btRAcHUkDRSIpwjhkYKtIgfb632V68MhQkBDQOlOfuaqC4-LhK6FOhSAkEiB0lBGkRDNgfI1uQv8BTNr391KQQhorPHu7OzOjj2PtXeWkFsF-NQyCHNP-gXzwEIxT4ui8lSqwoCpKkoF7h1-8FCsPY7ubfCNVmvP-Wtpu5-t5IPf7iv5H6lCGcgVd8n-g2SnRKEAYJAvXEHCcP0rGdOEU71KY0OTCK8qoYmmOqYxAILGPtWRBQCNITLgGGGR21ibKGoSagKaSKqheWQJ1s05VYyqVQskNI4dyhJbaWkpM1qfXjlxcJGmAgRjG0J3ygJtqgUC5o4dgLBVfCJtSxsG4luAIRZ0Av0btWyH3bZ1MEg9GQmjsVjGImTJNLxpy4CJqNHuaka9zbJRdxCqehhO1papVsdKRmAomjWRRl9HofNcakf5YvY5x5AHrD6m5oSRAJXDrJVIU0zYHoiVPLDn-c1s4vRPRSHww6Hi8hSZD6UMQHHO343vPzEznxPH5yhJrkEPOj6V4Jjzb3Yv8cu186kZ7hmbxXAQIWJKx-k9JvgXTszOgS3OMGau3Q2O6ZfsQmIzfU1qLWTy9kkWMYVId6u3-QwcI7tPrVelvU3HpVo_R842sdCSqR_s86Q16F4gZ5wMmReJN_o0PBru_Nw9HB-8G399Oxp-Pvp-8GN_7_jj69Hu4ejVm9HON6g93v8w_vL-Enm0mqy317zmhA8v5_guB1oVhWJlVilRgi8qfZ7pULCchymPNCtZWlQiS_280hIcy5IHKsqklLwKioJdJnO9rV55hSylJUxzWYW5n4aRyiGIr1iZ8zIr8rTMwmyBLE7Z7jyt87h0prJdIDebieg0b_eLzqDovsxw5nwNbvLVP7ZfJKcRs16Zu0bm-s-3y-vgq_azG83T8gvxSXA1 |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E5%9F%BA%E4%BA%8E%E9%9B%BE%E6%B0%94%E6%B5%93%E5%BA%A6%E4%BC%B0%E8%AE%A1%E7%9A%84%E5%9B%BE%E5%83%8F%E5%8E%BB%E9%9B%BE%E7%AE%97%E6%B3%95&rft.jtitle=%E8%87%AA%E5%8A%A8%E5%8C%96%E5%AD%A6%E6%8A%A5&rft.au=%E9%9E%A0%E9%93%AD%E7%83%A8+%E5%BC%A0%E7%99%BB%E9%93%B6+%E7%BA%AA%E5%BA%94%E5%A4%A9&rft.date=2016&rft.issn=0254-4156&rft.eissn=1874-1029&rft.volume=42&rft.issue=9&rft.spage=1367&rft.epage=1379&rft_id=info:doi/10.16383%2Fj.aas.2016.c150525&rft.externalDocID=669901857 |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fimage.cqvip.com%2Fvip1000%2Fqk%2F90250X%2F90250X.jpg http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fzdhxb%2Fzdhxb.jpg |