Articles | Volume 9, issue 2
Atmos. Meas. Tech., 9, 753–764, 2016
https://doi.org/10.5194/amt-9-753-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 9, 753–764, 2016
https://doi.org/10.5194/amt-9-753-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
01 Mar 2016
Research article
| 01 Mar 2016
From pixels to patches: a cloud classification method based on a bag of micro-structures
Qingyong Li et al.
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Cited
19 citations as recorded by crossref.
- Digital forensics of microscopic images for printed source identification M. Tsai & I. Yuadi 10.1007/s11042-017-4771-1
- Ground-Based Remote Sensing Cloud Classification via Context Graph Attention Network S. Liu et al. 10.1109/TGRS.2021.3063255
- Multi-Evidence and Multi-Modal Fusion Network for Ground-Based Cloud Recognition S. Liu et al. 10.3390/rs12030464
- FFT features and hierarchical classification algorithms for cloud images T. Kliangsuwan & A. Heednacram 10.1016/j.engappai.2018.08.008
- Supervised Fine-Grained Cloud Detection and Recognition in Whole-Sky Images L. Ye et al. 10.1109/TGRS.2019.2917612
- Dual Guided Loss for Ground-Based Cloud Classification in Weather Station Networks M. Li et al. 10.1109/ACCESS.2019.2916905
- Automatic Cloud-Type Classification Based On the Combined Use of a Sky Camera and a Ceilometer J. Huertas-Tato et al. 10.1002/2017JD027131
- DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features L. Ye et al. 10.1109/TGRS.2017.2712809
- A local binary pattern classification approach for cloud types derived from all-sky imagers S. Oikonomou et al. 10.1080/01431161.2018.1530807
- Analyzing of Cloud Macroscopic Characteristics in the Shigatse Area of the Tibetan Plateau Using the Total-Sky Images J. Yang et al. 10.1175/JAMC-D-18-0095.1
- Cloud classification of ground-based infrared images combining manifold and texture features Q. Luo et al. 10.5194/amt-11-5351-2018
- Cloud Type Classification of Total-Sky Images Using Duplex Norm-Bounded Sparse Coding J. Gan et al. 10.1109/JSTARS.2017.2669206
- Ground‐Based Cloud Classification Using Task‐Based Graph Convolutional Network S. Liu et al. 10.1029/2020GL087338
- Ground-Based Cloud-Type Recognition Using Manifold Kernel Sparse Coding and Dictionary Learning Q. Luo et al. 10.1155/2018/9684206
- Estimating Geo‐Referenced Cloud‐Base Height With Whole‐Sky Imagers B. Lyu et al. 10.1029/2019EA000944
- Intelligent classification of ground-based visible cloud images using a transfer convolutional neural network and fine-tuning M. Wang et al. 10.1364/OE.442455
- A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification Y. Wang et al. 10.1109/TGRS.2018.2866206
- CloudA: A Ground-Based Cloud Classification Method with a Convolutional Neural Network M. Wang et al. 10.1175/JTECH-D-19-0189.1
- Per-pixel classification of clouds from whole sky HDR images P. Satilmis et al. 10.1016/j.image.2020.115950
15 citations as recorded by crossref.
- Digital forensics of microscopic images for printed source identification M. Tsai & I. Yuadi 10.1007/s11042-017-4771-1
- Ground-Based Remote Sensing Cloud Classification via Context Graph Attention Network S. Liu et al. 10.1109/TGRS.2021.3063255
- Multi-Evidence and Multi-Modal Fusion Network for Ground-Based Cloud Recognition S. Liu et al. 10.3390/rs12030464
- FFT features and hierarchical classification algorithms for cloud images T. Kliangsuwan & A. Heednacram 10.1016/j.engappai.2018.08.008
- Supervised Fine-Grained Cloud Detection and Recognition in Whole-Sky Images L. Ye et al. 10.1109/TGRS.2019.2917612
- Dual Guided Loss for Ground-Based Cloud Classification in Weather Station Networks M. Li et al. 10.1109/ACCESS.2019.2916905
- Automatic Cloud-Type Classification Based On the Combined Use of a Sky Camera and a Ceilometer J. Huertas-Tato et al. 10.1002/2017JD027131
- DeepCloud: Ground-Based Cloud Image Categorization Using Deep Convolutional Features L. Ye et al. 10.1109/TGRS.2017.2712809
- A local binary pattern classification approach for cloud types derived from all-sky imagers S. Oikonomou et al. 10.1080/01431161.2018.1530807
- Analyzing of Cloud Macroscopic Characteristics in the Shigatse Area of the Tibetan Plateau Using the Total-Sky Images J. Yang et al. 10.1175/JAMC-D-18-0095.1
- Cloud classification of ground-based infrared images combining manifold and texture features Q. Luo et al. 10.5194/amt-11-5351-2018
- Cloud Type Classification of Total-Sky Images Using Duplex Norm-Bounded Sparse Coding J. Gan et al. 10.1109/JSTARS.2017.2669206
- Ground‐Based Cloud Classification Using Task‐Based Graph Convolutional Network S. Liu et al. 10.1029/2020GL087338
- Ground-Based Cloud-Type Recognition Using Manifold Kernel Sparse Coding and Dictionary Learning Q. Luo et al. 10.1155/2018/9684206
- Estimating Geo‐Referenced Cloud‐Base Height With Whole‐Sky Imagers B. Lyu et al. 10.1029/2019EA000944
4 citations as recorded by crossref.
- Intelligent classification of ground-based visible cloud images using a transfer convolutional neural network and fine-tuning M. Wang et al. 10.1364/OE.442455
- A Selection Criterion for the Optimal Resolution of Ground-Based Remote Sensing Cloud Images for Cloud Classification Y. Wang et al. 10.1109/TGRS.2018.2866206
- CloudA: A Ground-Based Cloud Classification Method with a Convolutional Neural Network M. Wang et al. 10.1175/JTECH-D-19-0189.1
- Per-pixel classification of clouds from whole sky HDR images P. Satilmis et al. 10.1016/j.image.2020.115950
Saved (final revised paper)
Latest update: 06 Feb 2023
Short summary
This paper proposes a new cloud classification method, named bag of micro-structures (BoMS), for whole-sky imagers. BoMS treats an all-sky image as a collection of micro-structures mapped from image patches, rather than a collection of pixels. BoMS identifies five different sky conditions: cirriform, cumuliform, stratiform, clear sky, and mixed cloudiness (often appearing in all-sky images but seldom addressed in the literature). The performance of BoMS overperforms those of traditional methods.
This paper proposes a new cloud classification method, named bag of micro-structures (BoMS), for...
