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Research article

MPFFNet: LULC classification model for high-resolution remote sensing images with multi-path feature fusion

, ORCID Icon, , , &
Pages 6089-6116 | Received 01 Jun 2023, Accepted 13 Sep 2023, Published online: 06 Oct 2023

References

  • AL-Alimi, D., Y. Shao, R. Feng, M. A. Al-Qaness, M. Abd Elaziz, and S. Kim. 2019. “Multi-Scale Geospatial Object Detection Based on Shallow-Deep Feature Extraction.” Remote Sensing 11 (21): 2525.
  • Alharbi, R., H. Alhichri, R. Ouni, Y. Bazi, and M. Alsabaan. 2023. “Improving Remote Sensing Scene Classification Using Quality-Based Data Augmentation.” International Journal of Remote Sensing 44 (6): 1749–1765.
  • Ardila, J. P., V. A. Tolpekin, W. Bijker, and A. Stein. 2011. “Markov-Random-Field-Based Super-Resolution Mapping for Identification of Urban Trees in VHR Images.” Isprs Journal of Photogrammetry & Remote Sensing 66 (6): 762–775.
  • Chen, L.-C. 2017. “Deeplab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected Crfs.” IEEE Transactions on Pattern Analysis & Machine Intelligence 40 (4): 834–848.
  • Cheng, G., and J. Han. 2016. “A Survey on Object Detection in Optical Remote Sensing Images.” Isprs Journal of Photogrammetry & Remote Sensing 117:11–28.
  • Chen, M., Y. Lingjie, C. Zhi, R. Sun, S. Zhu, Z. Gao, K. Zhenxia, M. Zhu, and Y. Zhang. 2022. “Improved Faster R-CNN for Fabric Defect Detection Based on Gabor Filter with Genetic Algorithm Optimization.” Computers in Industry 134:103551.
  • Chen, L.-C., G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille. 2014. “Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected Crfs.” arXiv preprint arXiv:1412.7062. https://doi.org/10.1109/CVPR.2014.264.
  • Chen, L.-C., G. Papandreou, F. Schroff, and H. Adam. 2017. “Rethinking Atrous Convolution for Semantic Image Segmentation.” arXiv preprint arXiv:1706.05587. https://doi.org/10.48550/arXiv.1706.05587.
  • Chen, L.-C., Y. Zhu, G. Papandreou, F. Schroff, and H. Adam. 2018. “Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.” Paper presented at the Proceedings of the European conference on computer vision (ECCV), Munich, Germany.
  • Cotter, A., J. Keshet, and N. Srebro. 2011. “Explicit Approximations of the Gaussian Kernel.” arXiv preprint arXiv:1109.4603. https://doi.org/10.48550/arXiv.1109.4603.
  • Dagher, I., and S. Abujamra. 2019. “Combined Wavelet and Gabor Convolution Neural Networks.” International Journal of Wavelets Multiresolution and Information Processing 17 (6): 1950046.
  • Danneels, G., E. Pirard, and H. B. Havenith. 2007. “Automatic Landslide Detection from Remote Sensing Images Using Supervised Classification Methods.” Paper presented at the IEEE International Geoscience & Remote Sensing Symposium, Barcelona, Spain.
  • Deng, Y., Z. Zhang, and X. Zhang. 2022. “A Novel Approach for Automatic Extraction Asphalt Pavement Sealed Crack.” Science Technology & Engineering 22 (16): 6687–6694.
  • Feng, D., Z. Zhang, and K. Yan. 2022. “A Semantic Segmentation Method for Remote Sensing Images Based on the Swin Transformer Fusion Gabor Filter.” IEEE Access 10:77432–77451.
  • Fu, H., X. Yanwu, D. Wing Kee Wong, and J. Liu. 2016. “Retinal Vessel Segmentation via Deep Learning Network and Fully-Connected Conditional Random Fields.” Paper presented at the 2016 IEEE 13th international symposium on biomedical imaging (ISBI), Miami, USA.
  • Gao, P., L. Jiatian, R. Yang, Z. Zhang, C. Yang, and X. Zhang. 2021. “Remote Sensing Images Segmentation Based on Low dimensional Texture Operator Combined with SLIC and Support Vector Machine Optimized by Double-Mutant Butterfly Optimization.” Geomatics and Information Science of Wuhan University 48 (1): 165–174. https://doi.org/10.13203/j.whugis20200496.
  • Gu, Y., Y. Wang, and Y. Li. 2019. “A Survey on Deep Learning-Driven Remote Sensing Image Scene Understanding: Scene Classification, Scene Retrieval and Scene-Guided Object Detection.” Applied Sciences 9 (10): 2110.
  • Hammouche, R., A. Attia, S. Akhrouf, and Z. Akhtar. 2022. “Gabor Filter Bank with Deep Autoencoder Based Face Recognition System.” Expert Systems with Applications 197:116743.
  • Han, Z., Y. Dian, H. Xia, J. Zhou, Y. Jian, C. Yao, X. Wang, and L. Yuan. 2020. “Comparing Fully Deep Convolutional Neural Networks for Land Cover Classification with High-Spatial-Resolution Gaofen-2 Images.” ISPRS International Journal of Geo-Information 9 (8): 478.
  • He, C., Y. Liu, D. Wang, S. Liu, Y. Linjun, and Y. Ren. 2023. “Automatic Extraction of Bare Soil Land from High-Resolution Remote Sensing Images Based on Semantic Segmentation with Deep Learning.” Remote Sensing 15 (6): 1646.
  • He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Las Vegas, USA.
  • Hu, P., F. Perazzi, F. Caba Heilbron, O. Wang, Z. Lin, K. Saenko, and S. Sclaroff. 2020. “Real-Time Semantic Segmentation with Fast Attention.” IEEE Robotics and Automation Letters 6 (1): 263–270.
  • Hu, Q., L. Zhang, D. Chen, W. Pedrycz, and Y. Daren. 2010. “Gaussian Kernel Based Fuzzy Rough Sets: Model, Uncertainty Measures and Applications.” International Journal of Approximate Reasoning 51 (4): 453–471.
  • Jamaluddin, I., T. Thaipisutikul, Y.-N. Chen, C.-H. Chuang, and H. Chih-Lin. 2021. “MDPrePost-Net: A Spatial-Spectral-Temporal Fully Convolutional Network for Mapping of Mangrove Degradation Affected by Hurricane Irma 2017 Using Sentinel-2 Data.” Remote Sensing 13 (24): 5042.
  • Knauer, U., M. S. Csv Rekowski, T. Krokotsch, and U. Seiffert. 2019. “Tree Species Classification Based on Hybrid Ensembles of a Convolutional Neural Network (CNN) and Random Forest Classifiers.” Remote Sensing 11 (23): 2788.
  • Kokila, S., and A. Jayachandran. 2023. “Hybrid Behrens-Fisher-And Gray Contrast–Based Feature Point Selection for Building Detection from Satellite Images.” Journal of Geovisualization and Spatial Analysis 7 (1): 8.
  • Li, X. 2012. “Object-Based Urban Vegetation Mapping with High-Resolution Aerial Photography as a Single Data Source.” International Journal of Remote Sensing 34 (3): 771–789.
  • Li, J., Y. Liu, J. Liu, R. Song, W. Liu, K. Han, and D. Qian. 2022. “Feature Guide Network with Context Aggregation Pyramid for Remote Sensing Image Segmentation.” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 15:9900–9912. https://doi.org/10.1109/JSTARS.2022.3221860.
  • Liu, Y., Z. Shao, Y. Teng, and N. Hoffmann. 2021. “NAM: Normalization-Based Attention Module.” arXiv preprint arXiv:2111.12419. https://doi.org/10.48550/arXiv.2111.12419.
  • Li, Y., L. Xiaojun, J. Song, Z. Wang, Y. He, and S. Yang. 2023. “Remote-Sensing-Based Change Detection Using Change Vector Analysis in Posterior Probability Space: A Context-Sensitive Bayesian Network Approach.” IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 16:3198–3217.
  • Longbotham, N. 2012. “Very High Resolution Multiangle Urban Classification Analysis.” IEEE Transactions on Geoscience & Remote Sensing 50 (4): 1155–1170.
  • Long, J., E. Shelhamer, and T. Darrell. 2015. “Fully Convolutional Networks for Semantic Segmentation.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Boston, USA.
  • Lovitt, J., G. Richardson, K. Rajaratnam, W. Chen, S. G. Leblanc, H. Liming, S. E. Nielsen, A. Hillman, I. Schmelzer, and A. Arsenault. 2022. “A New U-Net Based Convolutional Neural Network for Estimating Caribou Lichen Ground Cover from Field-Level RGB Images.” Canadian Journal of Remote Sensing 48 (6): 849–872.
  • Lv, S., L. Meng, D. Edwing, S. Xue, X. Geng, and X.-H. Yan. 2022. “High-Performance Segmentation for Flood Mapping of HISEA-1 SAR Remote Sensing Images.” Remote Sensing 14 (21): 5504.
  • Marmanis, D., K. Schindler, J. Dirk Wegner, S. Galliani, M. Datcu, and U. Stilla. 2018. “Classification with an Edge: Improving Semantic Image Segmentation with Boundary Detection.” Isprs Journal of Photogrammetry & Remote Sensing 135:158–172. https://doi.org/10.1016/j.isprsjprs.2017.11.009.
  • Martha, T. R., N. Kerle, C. J. van Westen, and V. Jetten. 2011. “Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis.” IEEE Transactions on Geoscience & Remote Sensing 49 (12): 4928–4943.
  • Nazarkevych, M., I. Klyujnyk, and H. Nazarkevych. 2018. “Investigation the Ateb-Gabor Filter in Biometric Security Systems.” Paper presented at the 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), Lviv Polytechnic National University, Ukraine.
  • Neupane, B., T. Horanont, and J. Aryal. 2021. “Deep Learning-Based Semantic Segmentation of Urban Features in Satellite Images: A Review and Meta-Analysis.” Remote Sensing 13 (4): 808. Remote Sensing (4). https://doi.org/10.3390/rs13040808.
  • Orlando, J. I., E. Prokofyeva, and M. B. Blaschko. 2016. “A Discriminatively Trained Fully Connected Conditional Random Field Model for Blood Vessel Segmentation in Fundus Images.” IEEE Transactions on Biomedical Engineering 64 (1): 16–27.
  • Panboonyuen, T., K. Jitkajornwanich, S. Lawawirojwong, P. Srestasathiern, and P. Vateekul. 2021. “Transformer-Based Decoder Designs for Semantic Segmentation on Remotely Sensed Images.” Remote Sensing 13 (24): 5100.
  • Peng, C., X. Zhang, Y. Gang, G. Luo, and J. Sun. 2017. “Large Kernel Matters–Improve Semantic Segmentation by Global Convolutional Network.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Honolulu, Hawaii.
  • Ramos, A. L. A., B. G. Dadiz, and A. Bernard G Santos. 2020. “Classifying Emotion Based on Facial Expression Analysis Using Gabor Filter: A Basis for Adaptive Effective Teaching Strategy.” Paper presented at the Computational Science and Technology: 6th ICCST 2019, Kota Kinabalu, Malaysia, 29-30 August 2019.
  • Ronneberger, O., P. Fischer, and T. Brox. 2015. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” Paper presented at the Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18.
  • Sahib, Z. A., O. Nuri Uçan, M. A. Talab, M. T. Alnaseeri, A. Hamid Mohammed, and H. Ali Sahib. 2020. “Hybrid Method Using EDMS & Gabor for Shape and Texture.” Paper presented at the 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA).
  • Sandler, M., A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen. 2018. “Mobilenetv2: Inverted Residuals and Linear Bottlenecks.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Salt Lake City, Utah.
  • Sarwar, S. S., P. Panda, and K. Roy. 2017. “Gabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks.” Paper presented at the 2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), Taipei, Taiwan.
  • Shirani, K., S. Solhi, and M. Pasandi. 2023. “Automatic Landform Recognition, Extraction, and Classification Using Kernel Pattern Modeling.” Journal of Geovisualization and Spatial Analysis 7 (1): 2.
  • Sun, X., X. Lin, S. Shen, and H. Zhanyi. 2017. “High-Resolution Remote Sensing Data Classification Over Urban Areas Using Random Forest Ensemble and Fully Connected Conditional Random Field.” ISPRS International Journal of Geo-Information 6 (8): 245.
  • Tong, X.-Y., L. Qikai, G.-S. Xia, and L. Zhang. 2018. “Large-Scale Land Cover Classification in Gaofen-2 Satellite Imagery.” Paper presented at the IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.
  • Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin. 2007. “Attention is All You Need.” In Advances in neural information processing systems. Paper presented at the Proc. NIPS, Vancouver, B.C., Canada.
  • Wang, D., R. Yang, H. Liu, H. Haiqing, J. Tan, L. Shaoda, Y. Qiao, K. Tang, and X. Wang. 2022. “HFENet: Hierarchical Feature Extraction Network for Accurate Landcover Classification.” Remote Sensing 14 (17): 4244.
  • Woo, S., J. Park, J.-Y. Lee, and I. So Kweon. 2018. “Cbam: Convolutional Block Attention Module.” Paper presented at the Proceedings of the European conference on computer vision (ECCV), Munich, Germany.
  • Yang, M., Y. Kun, C. Zhang, L. Zhiwei, and K. Yang. 2018. “Denseaspp for Semantic Segmentation in Street Scenes.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Salt Lake City, Utah.
  • Yang, X., L. Shanshan, Z. Chen, J. Chanussot, X. Jia, B. Zhang, L. Baipeng, and P. Chen. 2021. “An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery.” Isprs Journal of Photogrammetry & Remote Sensing 177:238–262.
  • Yang, S., F. Song, G. Jeon, and R. Sun. 2022. “Scene Changes Understanding Framework Based on Graph Convolutional Networks and Swin Transformer Blocks for Monitoring LCLU Using High-Resolution Remote Sensing Images.” Remote Sensing 14 (15): 3709.
  • Yan, K., and Z. Zhang. 2021. “Automated Asphalt Highway Pavement Crack Detection Based on Deformable Single Shot Multi-Box Detector Under a Complex Environment.” IEEE Access 9:150925–150938.
  • Yl, A., A. Dk, A. Yz, C. Ytb, and C. D. Ling. 2021. “Robust Deep Alignment Network with Remote Sensing Knowledge Graph for Zero-Shot and Generalized Zero-Shot Remote Sensing Image Scene Classification.” Isprs Journal of Photogrammetry & Remote Sensing 179:145–158.
  • Yu, C., J. Wang, C. Peng, C. Gao, Y. Gang, and N. Sang. 2018. “Learning a Discriminative Feature Network for Semantic Segmentation.” Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition, Salt Lake City, Utah.
  • Zhang, R., J. Chen, L. Feng, L. Shuang, W. Yang, and D. Guo. 2021. “A Refined Pyramid Scene Parsing Network for Polarimetric SAR Image Semantic Segmentation in Agricultural Areas.” IEEE Geoscience & Remote Sensing Letters 19:1–5.
  • Zhang, Z., C. Lan, W. Zeng, and Z. Chen. 2020. “Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-Based Person Re-Identification.” Paper presented at the Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, Seattle, USA.
  • Zhang, X., Z. Wang, L. Cao, and M. Wang. 2021. “A Remote Sensing Land Cover Classification Algorithm Based on Attention Mechanism.” Canadian Journal of Remote Sensing 47 (6): 835–845.
  • Zhang, Y., L. Weijun, L. Zhang, X. Ning, L. Sun, and L. Yaxuan. 2019. “Adaptive Learning Gabor Filter for Finger-Vein Recognition.” IEEE Access 7:159821–159830.
  • Zhang, Z., S. Zhang, H. Changtao, X. Zhang, S. Yang, H. Yan, and Z. Zhang. 2023. “Hazard Assessment Model of Ground Subsidence Coupling AHP, RS and GIS–A Case Study of Shanghai.” Gondwana Research 117:344–362.
  • Zhao, Q., J. Liu, L. Yuewen, and H. Zhang. 2021. “Semantic Segmentation with Attention Mechanism for Remote Sensing Images.” IEEE Transactions on Geoscience & Remote Sensing 60:1–13.
  • Zhao, H., J. Shi, X. Qi, X. Wang, and J. Jia. 2017. “Pyramid Scene Parsing Network.” Proceedings of the IEEE conference on computer vision and pattern recognition, Honolulu, Hawaii.
  • Zhao, H., Q. Xiaojuan, X. Shen, J. Shi, and J. Jia. 2018. “Icnet for Real-Time Semantic Segmentation on High-Resolution Images.” Paper presented at the Proceedings of the European conference on computer vision (ECCV), Munich, Germany.
  • Zhou, D., J. Tian, M. Luyao, and X. Sun. 2020. “Lightweight Image Semantic Segmentation Based on Multi-Level Feature Cascaded Network.” Journal of Zhejiang University (Engineering Science) 54 (8): 1516–1524.

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