This study proposed a fast variational detection method for stripe noise based on interval sampling, aiming to improve the detection efficiency of multi-column strip noise during the pushbroom imaging of mainstream satellites. Based on the variational modeling of stripe noise components and the optimal solution, this method can quickly determine stripe noise components through interval sampling and establishing an estimation model of stripe noise components with interval sampling parameters. Then, this method can locate the stripe noise through the one-dimensional outlier detection and post-processing of the column mean values of stripe noise components. Owing to the interval sampling strategy, the method proposed in this study significantly improves the detection efficiency without impairing the stripe noise detection accuracy.
白玉川, 徐锐, 李宗睿, 潘俊. 基于间隔采样的快速变分条带噪声检测方法[J]. 自然资源遥感, 2023, 35(3): 71-79.
BAI Yuchuan, XU Rui, LI Zongrui, PAN Jun. Fast variational detection of stripe noise based on interval sampling. Remote Sensing for Natural Resources, 2023, 35(3): 71-79.
Jiang G M, Niu Z, Ruan W L, et al. A study on removing the stripe noises in MODIS 1B images[J]. Remote Sensing Technology and Application, 2003(6):393-398.
[2]
曹艳丽. 高光谱图像条带噪声滤除技术的研究[D]. 哈尔滨: 哈尔滨工程大学, 2011.
Cao Y L. The research on filtering technology of stripe noise on hyperspectral image[D]. Harbin: Harbin Engineering University, 2011.
[3]
Zhang J, Xing L Y, Cui H L, et al. A new algorithm for stripe noises detection and removal in image processing[C]// Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series 891314, 2013:1-6.
[4]
Tsai F, Chen W W. Striping noise detection and correction of remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2008, 46(12):4122-4131.
doi: 10.1109/TGRS.2008.2000646
[5]
Liu Q H, Feng J. A destriping method combining strong filter with weak filter based on image divided and adapative strip noise detection[J]. Physics Procedia, 2012, 25:2103-2108.
doi: 10.1016/j.phpro.2012.03.356
[6]
胡旭东. 高分一号卫星遥感影像条带噪声检测与修复[D]. 武汉: 武汉大学, 2017.
Hu X D. Strip noise detecting and removal of GF-1 satellite images[D]. Wuhan: Wuhan University, 2017.
[7]
Horn B K P, Woodham R J. Destriping Landsat MSS images by histogram modification[J]. Computer Graphics and Image Processing, 1979, 10(1):69-83.
doi: 10.1016/0146-664X(79)90035-2
[8]
Cao B, Du Y, Xu D, et al. An improved histogram matching algorithm for the removal of striping noise in optical remote sensing imagery[J]. Optik - International Journal for Light and Electron Optics, 2015, 126(23):4723-4730.
doi: 10.1016/j.ijleo.2015.08.079
[9]
Gadallah F L, Csillag F, Smith E J M. Destriping multisensor imagery with moment matching[J]. International Journal of Remote Sensing, 2000, 21(12):2505-2511.
doi: 10.1080/01431160050030592
Xing K, Yue C Y, Liu S, et al. A spatial segmentation based moment matching satellite image stripe noise removal method:China,201310577168.4[P].2014-03-26.
[11]
Chen J, Lin H, Shao Y, et al. Oblique striping removal in remote sensing imagery based on wavelet transform[J]. International Journal of Remote Sensing, 2006, 27(8):1717-1723.
doi: 10.1080/01431160500185516
[12]
Zhao B, He B, Cong Y. Destriping method using lifting wavelet transform of remote sensing image[C]// 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering, 2010, 6:110-113.
[13]
Pan J J, Chang C I. Destriping of Landsat MSS images by filtering techniques[J]. Photogrammetric Engineering and Remote Sensing, 1992, 58(10):1417-1423
[14]
Chen J, Shao Y, Guo H, et al. Destriping CMODIS data by power filtering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(9):2119-2124.
doi: 10.1109/TGRS.2003.817206
[15]
Münch B, Trtik P, Marone F, et al. Stripe and ring artifact removal with combined wavelet-Fourier filtering[J]. Optics Express, 2009, 17(10):8567-8591.
doi: 10.1364/oe.17.008567
pmid: 19434191
[16]
Pande-Chhetri R, Abd-Elrahman A. De-striping hyperspectral imagery using wavelet transform and adaptive frequency domain filtering[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(5):620-636.
doi: 10.1016/j.isprsjprs.2011.04.003
[17]
Shen H F, Zhang L P. A map-based algorithm for destriping and inpainting of remotely sensed images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(5):1492-1502.
doi: 10.1109/TGRS.2008.2005780
[18]
Liu X, Lu X, Shen H, et al. Stripe noise separation and removal in remote sensing images by consideration of the global sparsity and local variational properties[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(5):1-12.
doi: 10.1109/TGRS.2015.2471975
[19]
Chen L, Sun D, Toh K C. A note on the convergence of ADMM for linearly constrained convex optimization problems[J]. Computational Optimization and Applications, 2017, 66:327-343.
doi: 10.1007/s10589-016-9864-7
[20]
Sun Y J, Huang T Z, Ma T H, et al. Remote sensing image stripe detecting and destriping using the joint sparsity constraint with iterative support detection[J]. Remote Sensing, 2019, 11(6):608.
doi: 10.3390/rs11060608
Wang C, Zhang Y S, Wang X, et al. Stripe noise removal of remote image based on wavelet variational method[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(8):1025-1037.
doi: 10.11947/j.AGCS.2019.20180394
[22]
赵书珩. 月球高光谱遥感影像复杂条带噪声处理的低秩方法研究[D]. 武汉: 武汉大学, 2021.
Zhao S H. Stripe noise removal for lunar hyperspectral imagery employing low-rank framework[D]. Wuhan: Wuhan University, 2021.
[23]
赵英时. 遥感应用分析原理与方法[M]. 北京: 科学出版社, 2003: 87-91.
Zhao Y S. Principles and methods of remote sensing application analysis[M]. Beijing: Science Press, 2003:87-91.
Yan X M, Hu X D, Yin S. Missing information detection on satellite remote sensing images[J]. Geomatics and Spatial Information Technology, 2020, 43(7):153-155,159.