145
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Completed homogeneous LBP for remote sensing image classification

ORCID Icon, & ORCID Icon
Pages 3815-3836 | Received 08 Feb 2023, Accepted 11 Jun 2023, Published online: 11 Jul 2023

References

  • Al Saidi, I., M. Rziza, and J. Debayle. 2020. “A New Texture Descriptor: The Homogeneous Local Binary Pattern (HLBP).” In International Conference on Image and Signal Processing, 308–316. Springer International Publishing. https://doi.org/10.1007/978-3-030-51935-3_33.
  • Al Saidi, I., M. Rziza, and J. Debayle. 2021a. “A Novel Texture Descriptor: Circular Parts Local Binary Pattern.” Image Analysis & Stereology 40 (2): 105–114. https://doi.org/10.5566/ias.2580.
  • Al Saidi, I., M. Rziza, and J. Debayle. 2021b. “A Novel Texture Descriptor: Homogeneous Rotated Local Binary Pattern (HRLBP).“ In 2020 10th International Symposium on Signal, Image, Video and Communications (ISIVC), Saint-Etienne, France, 1–5, IEEE. https://doi.org/10.1109/ISIVC49222.2021.9487538.
  • Al Saidi, I., M. Rziza, and J. Debayle. 2022. “A New LBP Variant: Corner Rhombus Shape LBP (CRSLBP).” Journal of Imaging 8 (7): 200.https://doi.org/10.3390/jimaging8070200.
  • Barakat, A., Z. Ouargaf, R. Khellouk, A. El Jazouli, and F. Touhami. 2019. “Land Use/Land Cover Change and Environmental Impact Assessment in Béni-Mellal District (Morocco) Using Remote Sensing and Gis.” Earth Systems and Environment 3 (1): 113–125. https://doi.org/10.1007/s41748-019-00088-y.
  • Bhagavathy, S., and B. S. Manjunath. 2006. “Modeling and Detection of Geospatial Objects Using Texture Motifs.” IEEE Transactions on Geoscience & Remote Sensing 44 (12): 3706–3715. https://doi.org/10.1109/TGRS.2006.881741.
  • Bing, T., W. Kuang, G. Zhao, H. Danbing, Z. Liao, and M. Weiwen 2019. “Hyperspectral Image Classification by Combining Local Binary Pattern and Joint Sparse Representation.” International Journal of Remote Sensing 40 (24): 9484–9500.https://doi.org/10.1080/01431161.2019.1633699.
  • Cai, W., and Z. Wei. 2020. “Remote Sensing Image Classification Based on a Cross-Attention Mechanism and Graph Convolution.” In IEEE Geoscience and Remote Sensing Letters, 1–5, http://doi.org/10.1109/LGRS.2020.3026587.
  • Chairet, R., Y. B. Salem, and M. Aoun. 2021. “Potential of Multi-Scale Completed Local Binary Pattern for Object Based Classification of Very High Spatial Resolution Imagery.” Journal of the Indian Society of Remote Sensing 49 (6): 1245–1255. https://doi.org/10.1007/s12524-021-01311-y.
  • Chen, C., B. Zhang, S. Hongjun, L. Wei, and L. Wang. 2016. “Land-Use Scene Classification Using Multi-Scale Completed Local Binary Patterns.” Signal, Image and Video Processing 10 (4): 745–752.https://doi.org/10.1007/s11760-015-0804-2.
  • Cheriyadat, A. M. 2013. “Unsupervised Feature Learning for Aerial Scene Classification.” IEEE Transactions on Geoscience & Remote Sensing 52 (1): 439–451.https://doi.org/10.1109/TGRS.2013.2241444.
  • Coburn, C. A., and A. C. Roberts. 2004. “A Multiscale Texture Analysis Procedure for Improved Forest Stand Classification.” International Journal of Remote Sensing 25 (20): 4287–4308. https://doi.org/10.1080/0143116042000192367
  • Emimal, M., and P. Kannan. 2018. “Classification of Remote Sensing Images Using Wavelet Based Contourlet Transform and Accuracy Analysis of Classified Images.” International Journal of Advanced Networking and Applications 9 (5): 3601–3605.
  • Fauvel, M., Y. Tarabalka, J. Atli Benediktsson, J. Chanussot, and J. C. Tilton. 2012. “Advances in Spectral-Spatial Classification of Hyperspectral Images.” Proceedings of the IEEE 101 (3): 652–675.https://doi.org/10.1109/JPROC.2012.2197589
  • González-Castro, V., J. Debayle, Y. Wazaefi, M. Rahim, C. Gaudy-Marqueste, J.-J. Grob, and B. Fertil. 2015. “Texture Descriptors Based on Adaptive Neighborhoods for Classification of Pigmented Skin Lesions.” Journal of Electronic Imaging 24 (6): 061104. https://doi.org/10.1117/1.JEI.24.6.061104
  • Guo, Z., L. Zhang, and D. Zhang. 2010. “A Completed Modeling of Local Binary Pattern Operator for Texture Classification.” IEEE Transactions on Image Processing 19 (6): 1657–1663. https://doi.org/10.1109/TIP.2010.2044957
  • Gupta, S., S. Kumar, A. Garg, D. Singh, and N. Singh Rajput. 2016. “Class Wise Optimal Feature Selection for Land Cover Classification Using SAR Data.” In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, IEEE, 68–71. https://doi.org/10.1109/IGARSS.2016.7729008.
  • Haifeng, L., K. Qiu, L. Chen, X. Mei, L. Hong, and C. Tao. 2020. “SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images.” IEEE Geoscience & Remote Sensing Letters 18 (5): 905–909.https://doi.org/10.1109/LGRS.2020.2988294.
  • Haitao, L., G. Haiyan, Y. Han, and J. Yang. 2010. “Object-Oriented Classification of High-Resolution Remote Sensing Imagery Based on an Improved Colour Structure Code and a Support Vector Machine.” International Journal of Remote Sensing 31 (6): 1453–1470.https://doi.org/10.1080/01431160903475266.
  • Huang, F., and L. Yan. 2015. “Hull Vector-Based Incremental Learning of Hyperspectral Remote Sensing Images.” Journal of Applied Remote Sensing 9 (1): 096022. https://doi.org/10.1117/1.JRS.9.096022.
  • Jenicka, S. 2019. “Sugeno Fuzzy-Inference-System-Based Land Cover Classification of Remotely Sensed Images.” In Environmental Information Systems: Concepts, Methodologies, Tools, and Applications, 1247–1283. IGI Global.https://doi.org/10.4018/978-1-5225-7033-2.ch057.
  • Jenicka, S., and A. Suruliandi. 2014. “Fuzzy Texture Model and Support Vector Machine Hybridization for Land Cover Classification of Remotely Sensed Images.” Journal of Applied Remote Sensing 8 (1): 083540. https://doi.org/10.1117/1.JRS.8.083540.
  • Jenicka, S., and A. Suruliandi. 2015. “Comparison of Soft Computing Approaches for Texture Based Land Cover Classification of Remotely Sensed Image.” Research Journal of Applied Sciences, Engineering & Technology 10 (10): 1216–1226. https://doi.org/10.19026/rjaset.10.1890.
  • Lucieer, A., A. Stein, and P. Fisher. 2005. “Multivariate Texture-Based Segmentation of Remotely Sensed Imagery for Extraction of Objects and Their Uncertainty.” International Journal of Remote Sensing 26 (14): 2917–2936. https://doi.org/10.1080/01431160500057723.
  • Lv, Z. et al., 2022. “Land Cover Change Detection with Heterogeneous Remote Sensing Images: Review, Progress, and Perspective.” In Proceedings of the IEEE, 1976–1991, https://doi.org/10.1109/JPROC.2022.3219376.
  • Nielsen, M. M. 2015. “Remote Sensing for Urban Planning and Management: The Use of Window-Independent Context Segmentation to Extract Urban Features in Stockholm.” Computers, Environment and Urban Systems 52:1–9. https://doi.org/10.1016/j.compenvurbsys.2015.02.002.
  • Ojala, T., T. Maenpaa, M. Pietikainen, J. Viertola, J. Kyllonen, and S. Huovinen. 2002. “Outex-New Framework for Empirical Evaluation of Texture Analysis Algorithms.” In 2002 International Conference on Pattern Recognition, Quebec City, QC, Canada, Vol. 1, 701–706. IEEE.
  • Ojala, T., M. Pietikäinen, and D. Harwood. 1996. “A Comparative Study of Texture Measures with Classification Based on Featured Distributions.” Pattern Recognition 29 (1): 51–59. https://doi.org/10.1016/0031-3203(95)00067-4.
  • Ojala, T., M. Pietikainen, and T. Maenpaa. 2002. “Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns.” IEEE Transactions on Pattern Analysis & Machine Intelligence 24 (7): 971–987. https://doi.org/10.1109/TPAMI.2002.1017623.
  • Ratajczak, R., C. Fernando Crispim-Junior, É. Faure, B. Fervers, and L. Tougne. 2019. “Automatic Land Cover Reconstruction from Historical Aerial Images: An Evaluation of Features Extraction and Classification Algorithms.” IEEE Transactions on Image Processing 28 (7): 3357–3371.https://doi.org/10.1109/TIP.2019.2896492.
  • Seng, C.-Y., S. Inbaraj, and Z. Sun. 2008. “Local Spatial Statistics for Remotely Sensed Image Classification of Mangrove.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 37.
  • Shengxiang, Q., M. Jie, J. Lin, L. Yansheng, and J. Tian. 2015. “Unsupervised Ship Detection Based on Saliency and S-HOG Descriptor from Optical Satellite Images.” IEEE Geoscience & Remote Sensing Letters 12 (7): 1451–1455.https://doi.org/10.1109/LGRS.2015.2408355.
  • Shu, L., and A. C. Chung. 2007. “Texture Classification by Using Advanced Local Binary Patterns and Spatial Distribution of Dominant Patterns.” In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing-ICASSP’07, Honolulu, HI, USA, Vol. 1, I–1221, IEEE. https://doi.org/10.1109/ICASSP.2007.366134.
  • Shu, L., M. W. Law, and A. C. Chung. 2009. “Dominant Local Binary Patterns for Texture Classification.” IEEE Transactions on Image Processing 18 (5): 1107–1118.https://doi.org/10.1109/TIP.2009.2015682.
  • Suruliandi, A. 2009. “Study on Classification of Remotely Sensed Multispectral Mages—A Textural Approach PhD Dissertation.” Manonmaniam Sundaranar University, Tamil Nadu, India.
  • Tabatabaei, S. M., and A. Chalechale. 2019. “Noise-Tolerant Texture Feature Extraction Through Directional Thresholded Local Binary Pattern.” The Visual Computer 967–987. 36 (5) https://doi.org/10.1007/s00371-019-01704-8.
  • Tan, X., and B. Triggs. 2010. “Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions.” IEEE Transactions on Image Processing 19 (6): 1635–1650. https://doi.org/10.1109/TIP.2010.2042645.
  • Tong, X.-Y., G.-S. Xia, L. Qikai, H. Shen, L. Shengyang, S. You, and L. Zhang. 2020. “Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Models.” Remote Sensing of Environment 237:111322.https://doi.org/10.1016/j.rse.2019.111322.
  • Vogiatzis, K. 2012. “Airport Environmental Noise Mapping and Land Use Management as an Environmental Protection Action Policy Tool. The Case of the Larnaka International Airport (Cyprus).” The Science of the Total Environment 424:162–173. https://doi.org/10.1016/j.scitotenv.2012.02.036.
  • Xia, G.-S., H. Jingwen, H. Fan, B. Shi, X. Bai, Y. Zhong, L. Zhang, and L. Xiaoqiang 2017. “AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification.” IEEE Transactions on Geoscience & Remote Sensing 55 (7): 3965–3981.https://doi.org/10.1109/TGRS.2017.2685945.
  • Yang, Y., and S. Newsam. 2008. “Comparing SIFT Descriptors and Gabor Texture Features for Classification of Remote Sensed Imagery.” In 2008 15th IEEE international conference on image processing, San Diego, CA, USA, 1852–1855, IEEE. https://doi.org/10.1109/ICIP.2008.4712139.
  • Yang, Y., and S. Newsam. 2010. “Bag-Of-Visual-Words and Spatial Extensions for Land-Use Classification.” In Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems (GIS '10). Association for Computing Machinery, New York, NY, USA, 270–279. https://doi.org/10.1145/1869790.1869829.
  • Yang, W., Y. Xiaoshuang, and G.-S. Xia. 2015. “Learning High-Level Features for Satellite Image Classification with Limited Labeled Samples.” IEEE Transactions on Geoscience & Remote Sensing 53 (8): 4472–4482.https://doi.org/10.1109/TGRS.2015.2400449.
  • Yang, R., X. Xin, X. Zhaozhuo, H. Dong, R. Gui, and P. Fangling 2019. “Dynamic Fractal Texture Analysis for PolSar Land Cover Classification.” IEEE Transactions on Geoscience & Remote Sensing 57 (8): 5991–6002.https://doi.org/10.1109/TGRS.2019.2903794.
  • Zhang, C., I. Sargent, X. Pan, L. Huapeng, A. Gardiner, J. Hare, and P. M. Atkinson. 2019. “Joint Deep Learning for Land Cover and Land Use Classification.” Remote Sensing of Environment 221:173–187.https://doi.org/10.1016/j.rse.2018.11.014.
  • Zhao, F., M. Xiaodong, Z. Yang, and Y. Zhaoxiang 2020. “A Novel Two-Stage Scene Classification Model Based on Feature Variable Significance in High-Resolution Remote Sensing.” Geocarto International 35 (14): 1603–1614.https://doi.org/10.1080/10106049.2019.1583772.
  • Zheng, G., L. Xiaofeng, L. Zhou, J. Yang, L. Ren, P. Chen, H. Zhang, and X. Lou. 2018. “Development of a Gray-Level Co-Occurrence Matrix-Based Texture Orientation Estimation Method and Its Application in Sea Surface Wind Direction Retrieval from SAR Imagery.” IEEE Transactions on Geoscience & Remote Sensing 56 (9): 5244–5260.https://doi.org/10.1109/TGRS.2018.2812778.
  • Zhiyong, L., H. Huang, L. Gao, J. Atli Benediktsson, M. Zhao, and C. Shi. 2022. “Simple Multiscale Unet for Change Detection with Heterogeneous Remote Sensing Images.” IEEE Geoscience & Remote Sensing Letters 19:1–5.https://doi.org/10.1109/LGRS.2020.3041409.
  • Zhiyong, L., F. Wang, G. Cui, J. Atli Benediktsson, T. Lei, and W. Sun. 2022. “Spatial–Spectral Attention Network Guided with Change Magnitude Image for Land Cover Change Detection Using Remote Sensing Images.” IEEE Transactions on Geoscience & Remote Sensing 60:1–12.https://doi.org/10.1109/TGRS.2022.3197901.
  • Zhiyong, L., F. Wang, W. Sun, Z. You, N. Falco, and J. Atli Benediktsson. 2022. “Landslide Inventory Mapping on VHR Images via Adaptive Region Shape Similarity.” IEEE Transactions on Geoscience & Remote Sensing 60:1–11.https://doi.org/10.1109/TGRS.2022.3204834.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.