Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

doi:10.11947/j.AGCS.2018.20170258

Abstract

Abstract: Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

Key words: remote sensing image, information recovery, image fusion, guided filter, transfer learning

CLC Number:

P237

HU Gensheng, ZHOU Wenli, LIANG Dong, BAO Wenxia. Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(3): 348-358.

References

[1] CAI Wenting,LIU Yongxue,LI Manchun,et al.A Self-adaptive Homomorphic Filter Method for Removing Thin Cloud[C]//Proceedings of 201119th International Conference on Geoinformatics.Shanghai:IEEE,2011:1-4.
[2] WU Xiaoping,YANG Wunian,LI Guoming.Thin Cloud Removal of ZY-3 Image based on Improved Homomorphism Filtering Method[C]//Proceedings of 201321st International Conference on Geoinformatics.Kaifeng:IEEE,2013:1-4.
[3] WANG Xia,LI Minmin,TANG Hongmei.A Modified Homomorphism Filtering Algorithm for Cloud Removal[C]//Proceedings of 2010 International Conference on Computational Intelligence and Software Engineering.Wuhan:IEEE,2010:1-4.
[4] SHEN Huandeng,LI Huifang,QIAN Yan,et al.An Effective Thin Cloud Removal Procedure for Visible Remote Sensing Images[J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,96:224-235.
[5] ZHU Xifang,WU Feng,TAO Chunkan.A New Algorithm of Cloud Removing for Optical Images Based on Wavelet Threshold Theory[J].Acta Photonica Sinica,2009,38(12):3312-3317.
[6] ZHU Xifang,WU Feng,ZHUANG Yanbin.An Improved Approach to Remove Cloud and Mist from Remote Sensing Digital Images Based on Mallat Algorithm[J].Journal of Remote Sensing,2007,11(2):241-246.
[7] 梁栋,孔颉,胡根生,等.基于支持向量机的遥感影像厚云及云阴影去除[J].测绘学报,2012,41(2):225-331,238. LIANG Dong,KONG Jie,HU Gensheng,et al.The Removal of Thick Cloud and Cloud Shadow of Remote Sensing Image Based on Support Vector Machine[J].Acta Geodaetica et Cartographica Sinica,2012,41(2):225-331,238.
[8] HU Gensheng,LI Xiaoyi,LIANG Dong.Thin Cloud Removal from Remote Sensing Images Using Multidirectional Dual Tree Complex Wavelet Transform and Transfer Least Square Support Vector Regression[J].Journal of Applied Remote Sensing,2015,9(1):095053.
[9] JEDLOVEC G J,HAINES S L,LAFONTAINE F J.Spatial and Temporal Varying Thresholds for Cloud Detection in GOES Imagery[J].IEEE Transactions on Geoscience and Remote Sensing,2008,46(6):1705-1717.
[10] EL-ARABY E,EL-GHAZAWI T,LE MOIGNE J,et al.Reconfigurable Processing for Satellite on-Board Automatic Cloud Cover Assessment[J].Journal of Real-Time Image Processing,2009,4(3):245-259.
[11] SHEN Yang,WANG Yong,LV Haitao,et al.Removal of Thin Clouds in Landsat-8 OLI Data with Independent Component Analysis[J].Remote Sensing,2015,7(9):11481-11500.
[12] GABARDA S,CRIST? BAL G.Cloud Covering Denoising through Image Fusion[J].Image and Vision Computing,2007,25(5):523-530.
[13] YANG Jun,ZHAO Zhongming,MA Jianglin,et al.Image Fusion for Automatic Detection and Removal of Clouds and Their Shadows[C]//Proceedings of SPIE Volume 6419,Geoinformatics 2006:Remotely Sensed Data and Information.Wuhan:SPIE,2006,6419:64191X.
[14] MENG Xiangchao,SHEN H,YUAN Qiangqiang,et al.An Integrated Fusion Framework for Joint Information Reconstruction and Resolution Enhancement[J].International Archives of the Photogrammetry,Remote Sensing and Spatial Information Sciences,2017,42:831-835.
[15] 许宁,肖新耀,尤红建,等.HCT变换与联合稀疏模型相结合的遥感影像融合[J].测绘学报,2016,45(4):434-441.DOI:10.11947/j.AGCS.2016.20150372. XU Ning,XIAO Xinyao,YOU Hongjian,et al.A Pansharpening Method based on HCT and Joint Sparse Model[J].Acta Geodaetica et Cartographica Sinica,2016,45(4):434-441.DOI:10.11947/j.AGCS.2016.20150372.
[16] KINGSBURY N Q,Kingsbury N.The Dual-Tree Complex Wavelet Transform:A New Technique for Shift Invariance and Directional Filters[C]//Proceedings of the 8th IEEE Digital Signal Processing Workshop.Bryce Canyon:IEEE.1998:2543-2560.
[17] CELIK T,TJAHJADI T.Image Resolution Enhancement Using Dual-tree Complex Wavelet Transform[J].IEEE Geoscience and Remote Sensing Letters,2010,7(3):554-557.
[18] 胡根生,査慧敏,梁栋,等.结合分类与迁移学习的薄云覆盖遥感图像地物信息恢复[J].电子学报,2017,45(12):2856-2862. HU Gensheng,ZHA Huimin,LIANG Dong,et al.Ground Object Information Recovery for Thin Cloud Contaminated Remote Sensing Images by Combining Classification with Transfer Learning[J].Acta Electronica Sinica,2017,45(12):2856-2862.
[19] HE Kaiming,SUN Jian,TANG Xiaoou.Guided Image Filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(6):1397-1409.
[20] HE Kaiming,SUN Jian,TANG Xiaoou.Single Image Haze Removal Using Dark Channel Prior[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(12):2341-2353.
[21] PAN S J,YANG Qiang.A Survey on Transfer Learning[J].IEEE Transactions on Knowledge and Data Engineering,2010,22(10):1345-1359.
[22] LAINE A F,ZONG Xuli.Multiscale Suboctave Wavelet Transform for Denoising and Enhancement[C]//Proceedings of SPIE Volume 2825,Wavelet Applications in Signal and Image Processing IV.Denver,CO:SPIE,1996,2825:238-249.
[23] KONG Jie,HU Gensheng,LIANG Dong.Thin Cloud Removing Approach of Color Remote Sensing Image based on Support Vector Machine[C]//Proceedings of 2010 Asia-Pacific Conference on Wearable Computing Systems.Shenzhen:IEEE,2010:131-135.
[24] HU Gensheng,SUN Xiaoqi,LIANG Dong,et al.Cloud Removal of Remote Sensing Image based on Multi-Output Support Vector Regression[J].Journal of Systems Engineering and Electronics,2014,25(6):1082-1088.
[25] DONOHO D L.De-noising by Soft-thresholding[J].IEEE Transactions on Information Theory,1995,41(3):613-627.
[26] HASHEMI M,BEHESHTI S.Adaptive Noise Variance Estimation in Bayes Shrink[J].IEEE Signal Processing Letters,2010,17(1):12-15.
[27] 胡根生,梁栋,孔颉.基于支持向量值轮廓波变换的遥感影像融合[J].电子学报,2010,38(6):1287-1292. HU Gensheng,LIANG Dong,KONG Jie.Remote Sensing Image Fusion Based on Support Vector Value Contourlet Transform[J].Acta Electronica Sinica,2010,38(6):1287-1292.