刘春国

• 1:河南理工大学测绘与国土信息工程学院

摘要(Abstract)：

针对Landsat MSS和TM多光谱图像上的散粒噪声问题,该文在分析其分布特点的基础上,提出了一种基于RX异常探测的噪声去除方法。视散粒噪声为光谱强异常,以RX算子探测异常,以光谱归一化方法定位散粒噪声。采用高同质化不规则的图像分割子区取代矩形窗计算RX异常,弱化小目标地物异常干扰采用不同噪声密度的MSS和TM多光谱图像开展算法验证。实验表明,此方法抑制了小目标地物异常,能有效去除MSS和TM多光谱图像上的散粒噪声,保留好像元,实现图像重建。

关键词(KeyWords)： 散粒噪声;Landsat多光谱图像;RX异常检测;超像素分割;图像去噪

Abstract:

Keywords:

基金项目(Foundation): 中国地质调查局地质调查项目(1212011120673)

作者(Author): 刘春国

DOI: 10.16251/j.cnki.1009-2307.2018.11.016

参考文献(References)：

• [1] WULDER M A,MASEK J G,COHEN W B,et al.Opening the archive:how free data has enabled the science and monitoring promise of Landsat[J].Remote Sensing of Environment,2012,122(1):2-10.
• [2]姜高珍,韩冰,高应波,等.Landsat系列卫星对地观测40年回顾及LDCM前瞻[J].遥感学报,2013,17(5):1033-1048.(JIANG Gaozhen,HAN Bing,GAO Yingbo,et al.Review of 40-year earth observation with Landsat series and prospects of LDCM[J].Journal of Remote Sensing,2013,17(5):1033-1048.)
• [3] WULDER M A,WHITE J C,GOWARD S N,et al.Landsat continuity:issues and opportunities for land cover monitoring[J].Remote Sensing of Environment,2008,112(3),955-969.
• [4] HUANG C Q,GOWARD S N,MASEK J G,et al.An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks[J].Remote Sensing of Environment,2010,114(1):183-198.
• [5] BRANDT J S,KUEMMERLE T,LI H M,et al.Using Landsat imagery to map forest change in southwest China in response to the national logging ban and ecotourism development[J].Remote Sensing of Environment,2012,121(138):358-369.
• [6] VITTEK M,BRINK A,DONNAY F,et al.Land cover change monitoring using Landsat MSS/TM satellite image data over West Africa between 1975and 1990[J].Remote Sensing,2013,6(1):658-676.
• [7] LIU L,TANG H,CACCETTA P,et al.Mapping afforestationand deforestation from 1974to 2012using Landsat time-series stacks in Yulin District,a key regionof the Three-North shelter region,China[J].Environmental Monitoring&Assessment,2013,185(12):9949-9965.
• [8] BARNES B B,HU C,HOLEKAMP K L,et al.Use of Landsat data to track historical water quality changes in Florida keys marine environments[J].Remote Sensing of Environment,2014,140(1):485-496.
• [9]王颖洁,刘良云,王志慧.基于时序Landsat数据的三江平原植被地表类型变化遥感探测研究[J].遥感技术与应用,2015,30(5):959-968.(WANG Yingjie,LIU Liangyun,WANG Zhihui.Land cover mapping based on Landsat time-series stacks in Sanjiang Plain[J].Remote Sensing Technology and Application,2015,30(5):959-968.)
• [10]张志杰,张浩,常玉光,等.Landsat系列卫星光学遥感器辐射定标方法综述[J].遥感学报,2015,19(5):719-732.(ZHANG Zhijie,ZHANG Hao,CHANG Yuguang,et al.Review of radiometric calibration methods of Landsat series optical remote sensors[J].Journal of Remote Sensing,2015,19(5):719-732.)
• [11]JENSEN J R.Introductory digital image processing:a remote sensing perspective[M].3rd ed.Upper Saddle River,N.J:Prentice Hall,2005:185-188.
• [12]王立海,赵正勇.林区TM图像消除噪声方法的比较[J].东北林业大学学报,2005,33(5):77-79.(WANG Lihai,ZHAO Zhengyong.Comparative study on the denoising methods of TM images for forest regions[J].Journal of Northeast Forestry University,2005,33(5):77-79.)
• [13]宋国大,黄文骞,张梅彩,等.海洋TM卫星影像噪声探测与去除方法研究[J].海洋测绘,2013,33(2):42-44,52.(SONG Guoda,HUANG Wenqian,ZHANG Meicai,et al.Methods for detecting and removing noise of ocean multi-spectral images[J].Hydrographic Surveying and Charting,2013,33(2):42-44,52.)
• [14]ZHANG M,CARDER K,MULLER-KARGER F E,et al.Noise reduction and atmospheric correction for coastal applications of Landsat thematic mapper imageryregion 9,florida west coast and the keys[J].Remote Sensing of Environment,1999,70(2):167-180.
• [15]王昱,张广友,李新涛,等.卫星遥感影像预处理中噪声去除方法的研究[J].遥感技术与应用,2007,22(3):455-459.(WANG Yu,ZHANG Guangyou,LI Xintao,et al.Research on noise remove method of preprocess satellite remote sensing image[J].Remote Sensing Technology and Application,2007,22(3):455-459.)
• [16]CAI S,DU Q,MOORHEAD R J.Hyperspectral imagery visualization using double layers[J].IEEE Transactions on Geoscience&Remote Sensing,2007,45(10):3028-3036.
• [17]HAN T,GOODENOUGH D G,DYK A,et al.Detection and correction of abnormal pixels in Hyperion images[C]//Geoscience and Remote Sensing Symposium.Toronto:IEEE,2002:1327-1330.
• [18]CHANG C I,CHIANG S S.Anomaly detection and classification for hyperspectral imagery[J].Transactions on Geoscience and Remote Sensing,2002,40(6):1314-1325.
• [19]REED I S,YU X.Adaptive multiple-band CFAR detectionof an optical pattern with unknown spectral distribution[J].IEEE Transactions on Acoustics Speech&Signal Processing,1990,38(10):1760-1770.
• [20]ROSSI A,ACITO N,DIANI M,et al.RX architectures for real-time anomaly detection in hyperspectral images[J].Journal of Real-Time Image Processing,2014,9(3):503-517.
• [21]ASHTON E A,SCHAUM A.Algorithms for the detection of sub-pixel targets in multispectral imagery[J].Photogrammetric Engineering&Remote Sensing,1998,64(7):723-731.
• [22]CHEN C M,HEPNER G F,FORSTER R R.Fusion of hyperspectral and radar data using the IHS transformation to enhance urban surface features[J].ISPRS Journal of Photogrammetry&Remote Sensing,2003,58(1):19-30.
• [23]GREEN A A,BERMAN M,SWITZER P,et al.A transformation for ordering multispectral data in terms of image quality with implications for noise removal[J].IEEE Transactions on Geoscience&Remote Sensing,1988,26(1):65-74.
• [24]GONZALEZ R C,WOODS R E.数学图像处理[M].3rd,ed.阮秋琦,阮宇智,译.北京:电子工业出版社,2011:407-436.(GONZALEZ R C,WOODS R E.Digital image processing[M].3rd ed.RUAN Q Q,RUAN Y Z,translate.Beijing:Publishing House of Electronics Industry,2011:407-436.)
• [25]LEVINSHTEIN A,STERE A,KUTULAKOS K N,et al.Turbo pixels:fast superpixels using geometric flows[J].IEEE Transactions on Pattern Analysis&MachineIntelligence,2009,31(12):2290-2297.
• [26]ACHANTA R,SHAJI A,SMITH K,et al.SLIC superpixels compared to state of the art superpixel methods[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2012,34(11):2274-2282.
• [27]QIN C,ZHANG G,ZHOU Y,et al.Integration of the saliency-based seed extraction and random walks for image segmentation[J].Neurocomputing,2014,129(4):378-391.
• [28]BERGH M V D,BOIX X,ROIG G,et al.SEEDS:superpixelsextracted via energy-driven sampling[C]//The 12th European Conference on Computer Vision.[S.l.]:[s.n.],2012.