Scattering and contextual features fusion using a complex multi-scale decomposition for polarimetric SAR image classification

References

• Ahmed N, Saha S, Shahzad M, Fraz MM, Xiang Zhu X. 2021. Progressive unsupervised deep transfer learning for forest mapping in satellite image. 2021 IEEE/CVF International Conference on Computer Vision Workshops, p. 752–761.
   Google Scholar
• Bishop CM. 2006. Pattern recognition and machine learning. Berlin: Springer.
   Google Scholar
• Chang H-H, Yeh C-H. 2022. Face anti-spoofing detection based on multi-scale image quality assessment. Image Vis Comput. 121:104428.
   Web of Science ®Google Scholar
• Chen Y, Li L, Jiao L, Li Y, Liu X, Chai X. 2021. Nonlinear projective dictionary pair learning for PolSAR image classification. IEEE Access. 9:70650–70661.
   Web of Science ®Google Scholar
• Cloude SR, Pottier E. 1997. An entropy based classification scheme for land applications of polarimetric SAR. IEEE Trans Geosci Remote Sens. 35(1):68–78.
   Web of Science ®Google Scholar
• Cui Y, Liu F, Jiao L, Guo Y, Liang X, Li L, Yang S, Qian X. 2022. Polarimetric multipath convolutional neural network for PolSAR image classification. IEEE Trans Geosci Remote Sens. 60(5207118):1–18.
   Google Scholar
• Geng J, Deng X, Ma X, Jiang W. 2020. Transfer learning for SAR image classification via deep joint distribution adaptation networks. IEEE Trans Geosci Remote Sens. 58(8):5377–5392.
   Web of Science ®Google Scholar
• Ghassemi M, Ghassemian H, Imani M. 2021. Hyperspectral image classification by optimizing convolutional neural networks based on information theory and 3D-gabor filters. Int J Remote Sens. 42(11):4380–4410.
   Web of Science ®Google Scholar
• Guo J, Wang L, Zhu D, Zhang G. 2022. Semisupervised classification of PolSAR images using a novel memory convolutional neural network. IEEE Geosci Remote Sens Lett. 19(4007605):1–5.
   Google Scholar
• Guo Y, Han S, Li Y, Zhang C, Bai Y. 2018. K-nearest neighbor combined with guided filter for hyperspectral image classification. Procedia Comput Sci. 129:159–165.
   Google Scholar
• Han K, Jiang M, Wang M, Liu G. 2018. Compact polarimetric SAR interferometry target decomposition with the Freeman–Durden method. IEEE J Sel Top Appl Earth Observ Remote Sens. 11(8):2847–2861.
   Web of Science ®Google Scholar
• Han W, Fu H, Zhu J, Wang C, Xie Q. 2022. Polarimetric SAR decomposition by incorporating a rotated dihedral scattering model. IEEE Geosci Remote Sens Lett. 19(4005505):1–5.
   Google Scholar
• Imani M. 2021a. Integration of the k-nearest neighbours and patch-based features for PolSAR image classification by using a two-branch residual network. Remote Sens Lett. 12(11):1112–1122.
   Web of Science ®Google Scholar
• Imani M. 2021b. Polarimetric SAR classification using ridge regression-based polarimetric-spatial feature extraction. 26th International Computer Conference, Computer Society of Iran, Tehran, Iran.
   Google Scholar
• Imani M. 2021c. A random patches based edge preserving network for land cover classification using polarimetric synthetic aperture radar images. Int J Remote Sens. 42(13):4942–4960.
   Web of Science ®Google Scholar
• Imani M. 2022. Median-mean line based collaborative representation for PolSAR terrain classification. Egypt J Remote Sens Space Sci. 25(1):281–288.
   Web of Science ®Google Scholar
• Imani M, Ghassemian H. 2013. The investigation of sensitivity of SVM classifier respect to the number of features and the number of training samples. 2nd International Conference on Sensors and Models in Photogrammetry and Remote Sensing, SMPR 2013, Tehran, Iran, pp. 209–214.
   Google Scholar
• Imani M, Ghassemian H. 2019. Morphology-based structure-preserving projection for spectral–spatial feature extraction and classification of hyperspectral data. IET Image Process. 13(2):270–279.
   Web of Science ®Google Scholar
• Kang X, Li S, Benediktsson JA. 2014. Spectral–spatial hyperspectral image classification with edge-preserving filtering. IEEE Trans Geosci Remote Sens. 52(5):2666–2677.
   Web of Science ®Google Scholar
• Kuo BC, Landgrebe DA. 2004. Nonparametric weighted feature extraction for classification. IEEE Trans Geosci Remote Sens. 42(5):1096–1105.
   Web of Science ®Google Scholar
• Lewis JJ, O’Callaghan RJ, Nikolov SG, Bull DR, Canagarajah N. 2007. Pixel- and region-based image fusion with complex wavelets. Inf Fusion. 8(2):119–130.
   Web of Science ®Google Scholar
• Li J, Huang X, Gamba P, Bioucas-Dias JM, Zhang L, Benediktsson JA, Plaza A. 2015. Multiple feature learning for hyperspectral image classification. IEEE Trans Geosci Remote Sens. 53(3):1592–1606.
   Web of Science ®Google Scholar
• Li L, Ma L, Jiao L, Liu F, Sun Q, Zhao J. 2020. Complex contourlet-CNN for polarimetric SAR image classification. Pattern Recognit. 100:107110.
   Web of Science ®Google Scholar
• Li L, Zhang X, Zhou Y, Pu L, Shi J, Wei S. 2021b. Region adaptive morphological reconstruction fuzzy C-means for near-field 3-D SAR image target extraction. Digit Signal Process. 113:103036.
   Web of Science ®Google Scholar
• Li X, Ouyang L, Hui F, Cheng X, Shokr M, Heil P. 2018. An improved automated method to detect landfast ice edge off Zhongshan Station using SAR imagery. IEEE J Sel Top Appl Earth Observ Remote Sens. 11(12):4737–4746.
   Web of Science ®Google Scholar
• Li Y, Li Z, Zhang C, Luo Z, Zhu Y, Ding Z, Qin T. 2021a. Infrared maritime dim small target detection based on spatiotemporal cues and directional morphological filtering. Infrared Phys Technol. 115:103657.
   Web of Science ®Google Scholar
• Liu F, Shi J, Jiao L, Liu H, Yang S, Wu J, Hao H, Yuan J. 2016. Hierarchical semantic model and scattering mechanism based PolSAR image classification. Pattern Recognit. 59:325–342.
   Web of Science ®Google Scholar
• Liu X, Liu Q, Wang Y. 2020. Remote sensing image fusion based on two-stream fusion network. Inf Fusion. 55:1–15.
   Web of Science ®Google Scholar
• Liu Y, Liu S, Wang Z. 2015. A general framework for image fusion based on multi-scale transform and sparse representation. Inf Fusion. 24:147–164.
   Web of Science ®Google Scholar
• Luo S, Sarabandi K, Tong L, Pierce L. 2019. A SAR image classification algorithm based on multi-feature polarimetric parameters using FOA and LS-SVM. IEEE Access. 7:175259–175276.
   Web of Science ®Google Scholar
• Mehra A, Jain N, Srivastava HS. 2022. A novel approach to use semantic segmentation based deep learning networks to classify multi-temporal SAR data. Geocarto Int. 37(1):163–178.
   Web of Science ®Google Scholar
• Memon N, Parikh H, Patel SB, Patel D, Patel VD. 2021. Automatic land cover classification of multi-resolution dualpol data using convolutional neural network (CNN). Remote Sens Appl: Soc Environ. 22:100491.
   Google Scholar
• Molaei S, Shiri Ahmad Abadi ME. 2020. Maintaining filter structure: a Gabor-based convolutional neural network for image analysis. Appl Soft Comput. 88:105960.
   Web of Science ®Google Scholar
• Moya L, Zakeri H, Yamazaki F, Liu W, Mas E, Koshimura S. 2019. 3D gray level co-occurrence matrix and its application to identifying collapsed buildings. ISPRS J Photogramm Remote Sens. 149:14–28.
   Web of Science ®Google Scholar
• Mukherjee A, Misra S, Raghuwanshi NS. 2019. A survey of unmanned aerial sensing solutions in precision agriculture. J Netw Comput Appl. 148:102461.
   Web of Science ®Google Scholar
• O’Callaghan RJ, Bull DR. 2005. Combined morphological-spectral unsupervised image segmentation. IEEE Trans Image Process. 14(1):49–62.
   PubMed Web of Science ®Google Scholar
• Padmavathi K, Bhat M, Karki MV. 2017. Feature selection based on PCA and PSO for multimodal medical image fusion using DTCWT. arXiv:1701.08918.
   Google Scholar
• Pal M. 2012. Multinomial logistic regression-based feature selection for hyperspectral data. Int J Appl Earth Obs Geoinf. 14(1):214–220.
   Web of Science ®Google Scholar
• Paradzayi C, Annegarn HJ, Matsika R, Erasmus B. 2008. Field surveys for biomass assessment in African savanna woodlands. IGARSS 2008–2008 IEEE International Geoscience and Remote Sensing Symposium. III-632–III-635.
   Google Scholar
• Park S, Moon WM. 2007. Unsupervised classification of scattering mechanisms in polarimetric SAR data using fuzzy logic in entropy and alpha plane. IEEE Trans Geosci Remote Sens. 45(8):2652–2664.
   Web of Science ®Google Scholar
• Raj JA, Idicula SM, Paul B. 2022. One-shot learning-based SAR ship classification using new hybrid Siamese network. IEEE Geosci Remote Sens Lett. 19(4017205):1–5.
   Google Scholar
• Ren H, Chang Y-L. 2005. Feature extraction with modified Fisher’s linear discriminant analysis. Proc. SPIE 5995. Chemical and Biological Standoff Detection III, 599506.
   Google Scholar
• Rostami M, Kolouri S, Eaton E, Kim K. 2019. Deep transfer learning for few-shot SAR image classification. Remote Sens. 11(11):1374.
   Google Scholar
• Salehi M, Sahebi MR, Maghsoudi Y. 2014. Improving the accuracy of urban land cover classification using Radarsat-2 PolSAR data. IEEE J Sel Top Appl Earth Observ Remote Sens. 7(4):1394–1401.
   Web of Science ®Google Scholar
• Shang R, He J, Wang J, Xu K, Jiao L, Stolkin R. 2020. Dense connection and depthwise separable convolution based CNN for polarimetric SAR image classification. Knowl-Based Syst. 194:105542.
   Web of Science ®Google Scholar
• Shi J, Jin H, Li X. 2020. A novel multi-feature joint learning method for fast polarimetric SAR terrain classification. IEEE Access. 8:30491–30503.
   Google Scholar
• Song W, Wu Y, Guo P. 2021a. Composite kernel and hybrid discriminative random field model based on feature fusion for PolSAR image classification. IEEE Geosci Remote Sens Lett. 18(6):1069–1073.
   Web of Science ®Google Scholar
• Song W, Wu Y, Xiao X. 2021b. Nonstationary PolSAR image classification by deep-features-based high-order triple discriminative random field. IEEE Geosci Remote Sens Lett. 18(8):1406–1410.
   Web of Science ®Google Scholar
• Sukawattanavijit C, Chen J, Zhang H. 2017. GA-SVM algorithm for improving land-cover classification using SAR and optical remote sensing data. IEEE Geosci Remote Sens Lett. 14(3):284–288.
   Web of Science ®Google Scholar
• Tang R, Xu X, Yang R, Gui R. 2021. Deep graph cluster based unsupervised representation learning for PolSAR image classification. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, p. 4252–4255.
   Google Scholar
• Turkar V, Checker J, De S, Singh G. 2022. Impact of G4U and 7-component target decomposition on PolSAR image semantic segmentation. Adv Space Res. https://www.sciencedirect.com/science/article/abs/pii/S0273117722004136
   PubMed Web of Science ®Google Scholar
• Uppala D, Somepalli V, Venkata RK, Rama SMV. 2021. Identification of optimal single date for rice crop discrimination and relationships between backscatter and biophysical parameters using RISAT-1 hybrid polarimetric SAR data. Geocarto Int. 36(17):2010–2022.
   Web of Science ®Google Scholar
• Wang F, Ainouz S, Lian C, Bensrhair A. 2017. Multimodality semantic segmentation based on polarization and color images. Neurocomputing. 253:193–200.
   Web of Science ®Google Scholar
• Wang J, Hou B, Ren B, Zhang Y, Yang M, Wang S, Jiao L. 2022b. Parameter selection of Touzi decomposition and a distribution improved autoencoder for PolSAR image classification. ISPRS J Photogramm Remote Sens. 186:246–266.
   Web of Science ®Google Scholar
• Wang X, Zhu D, Li G, Zhang X-P, He Y. 2022c. Proposal-copula-based fusion of spaceborne and airborne SAR images for ship target detection. Inf Fusion. 77:247–260.
   Web of Science ®Google Scholar
• Wang Y, Cheng J, Zhou Y, Zhang F, Yin Q. 2022a. A multichannel fusion convolutional neural network based on scattering mechanism for PolSAR image classification. IEEE Geosci Remote Sens Lett. 19(4007805):1–5.
   Google Scholar
• Xie W, Ma G, Zhao F, Liu H, Zhang L. 2020. PolSAR image classification via a novel semi-supervised recurrent complex-valued convolution neural network. Neurocomputing. 388:255–268.
   Web of Science ®Google Scholar
• Xu Y, Lang H, Niu L, Ge C. 2019. Discriminative adaptation regularization framework-based transfer learning for ship classification in SAR images. IEEE Geosci Remote Sens Lett. 16(11):1786–1790.
   Web of Science ®Google Scholar
• Zhang F, Yan M, Hu C, Ni J, Zhou Y. 2022. Integrating coordinate features in CNN-based remote sensing imagery classification. IEEE Geosci Remote Sens Lett. 19(5502505):1–5.
   Google Scholar
• Zhang L, Dong H, Zou B. 2019a. Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework. ISPRS J Photogramm Remote Sens. 157:59–72.
   Web of Science ®Google Scholar
• Zhang L, Jiao L, Ma W, Duan Y, Zhang D. 2019b. PolSAR image classification based on multi-scale stacked sparse autoencoder. Neurocomputing. 351:167–179.
   Web of Science ®Google Scholar
• Zhang X, Li Y, Kotagiri R, Wu L, Tari Z, Cheriet M. 2017. KRNN: k rare-class nearest neighbour classification. Pattern Recognit. 62:33–44.
   Web of Science ®Google Scholar
• Zhang Y, Sidibé D, Morel O, Mériaudeau F. 2021. Deep multimodal fusion for semantic image segmentation: A survey. Image Vis Comput. 105:104042.
   Web of Science ®Google Scholar
• Zhao J, Datcu M, Zhang Z, Xiong H, Yu W. 2019. Contrastive-regulated CNN in the complex domain: A method to learn physical scattering signatures from flexible PolSAR images. IEEE Trans Geosci Remote Sens. 57(12):10116–10135.
   Web of Science ®Google Scholar
• Zheng Y-g, Zhang H-s, Qi K-t, Ding L-y. 2021. Stripe segmentation of oceanic internal waves in SAR images based on SegNet. Geocarto Int.: 1–12. https://www.tandfonline.com/doi/full/10.1080/10106049.2021.2002430
   Web of Science ®Google Scholar