期刊文献+

遥感影像超分辨率制图研究进展 被引量:4

Research progress in super-resolution mapping from remotely sensed imagery
原文传递
导出
摘要 尺度问题是土地覆盖分类中的一个核心问题,向下尺度转换又是其中的难点。混合像元分解可以得到亚像元尺度的类别组分百分比,但无法求得亚像元的具体位置。遥感影像超分辨率制图是由粗空间分辨率的影像得到高空间分辨率分类结果图的技术,可用于地表分类向下尺度转换,近年来该技术已成为遥感影像分类和尺度转换领域的研究热点。对超分辨率制图研究进展做了详细论述,从超分辨率制图的发展和研究现状、主要方法、精度评价等几方面进行了详细阐述,并分析了当前超分辨率制图算法存在的主要问题,以及可能的研究重点和发展空间。 Scale problem is one of the central issues in land cover mapping from remote sensing imagery, and downscaling land cover data is a difficulty in this domain. Soft classification can provide more information than hard classification at pixel level. However, the spatial location of land cover compositions within each pixel is unknown. To solve this problem, many super-resolution mapping methods have been developed in recent years. In this paper, a review on recent development of super-resolution mapping methods is presented. The review focuses on the research status, major algorithms and accuracy assessment methods of super-resolution mapping. The main drawbacks, research challenges and future directions of super-resolution mapping are discussed.
出处 《中国图象图形学报》 CSCD 北大核心 2011年第4期495-502,共8页 Journal of Image and Graphics
基金 国家自然科学基金(40871163 40871161) 国家重点基础研究发展(973)计划项目(2007CB714407 2007CB714402) 遥感科学国家重点实验室开放基金 国土资源部百名优秀青年科技人才计划 保定市科学技术研究与发展指导计划(10ZF005)
关键词 超分辨率 亚像元 制图 分类 尺度转换 super-resolution sub-pixel mapping classification scaling
  • 相关文献

参考文献49

  • 1Bastin L.Comparison of fuzzy c-means classification,linear mixture modelling and MLC probabilities as tools for unmixing coarse pixels[J].International Journal of Remote Sensing,1997,18(17):3629-3648.
  • 2Adams J B,Smith M O,Johnson P E.Spectral mixture modelling:a new analysis of rock and soil types at the Viking Lander 1 site[J].Journal of Geophysical Research,1986,91 (Bg):8098-8112.
  • 3Garca-Haro F J,Gilabert M A,Melia J.Linear spectral mixture modelling to estimate vegetation amount from optical spectral data[J].International Journal of Remote Sensing,1996,17(17):3373-3400.
  • 4Kanellopoulos I,Varfis A,Wilkinson G G,et al.Land cover discrimination in SPOT HRV imagery using an artificial neural network:a 20 class experiment[J].International Journal of Remote Sensing,1992,13 (5):917-924.
  • 5Bezdek J C,Ehrlich R,Full W.FCM:The fuzzy c-meansclustering algorithm[J].Computers & Geosciences,1984,10(2-3):191-203.
  • 6Bezdek J.Pattern Recognition with Fuzzy Objective Function Algorithms[M].New York:Plenum Press,1981.
  • 7Foody G M,Cox D P.Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions[J].International Journal of Remote Sensing,1994,15(3):619-631.
  • 8Boucher A.Super Resolution Mapping With Multiple Point Geostatistics[M]// Pereira M J,Soares A,Dimitrakopoulos R.GeoENV VI-Geostatistics for Environmental Applications.Netherlands:Springer,2008:297-305.
  • 9Atkinson P M.Issues of uncertainty in super-resolution mapping and the design of an inter-comparison study[C]//Zhang J,Goodchild M F.Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences.Liverpool,England,UK:World Academic,2008:145-154.
  • 10He Y,Yap K H,Chen L,et al.A soft MAP framework for blind super-resolution image reconstruction[J].Image and Vision Computing,2009,27(4):364-373.

二级参考文献49

  • 1易嫦,潘耀忠,张锦水.基于多尺度空间ANN-CA模型的遥感影像超分辨率制图方法研究[J].地理与地理信息科学,2007,23(3):42-46. 被引量:6
  • 2周成虎 孙战利 谢一春.地理元胞自动机研究[M].北京:科学出版社,2001.34-38.
  • 3Boucher A. Super resolution mapping with multiple point geosta tistics. In: Pereira MJ, Soares A, Dimitrakopoulos R, eds. GeoENV VI-Geostatistics for Environmental Applications. Netherlands: Springer 2008, 297--305.
  • 4Atkinson PM. Issues of uncertainty in super-resolution mapping and the design of an inter-comparison study. In: Zhang J, Goodchild MF, eds. Spatial Uncertainty. Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Nat ural Resources and Environmental Sciences. Shanghai, China: World Academic Press, 2008, 145--154.
  • 5Aplin P, Atkinson PM. Sub-pixel land cover mapping for perfield classification. International Journal of Remote Sensing, 2001, 22(14): 2853--2858.
  • 6Ge Y, Li S, Li D. New algorithm for sub-pixel boundary mapping. In: International Archives of Photogrammetry, Remote Sensing, and Spatial Information Sciences. Vienna, 2006,157-- 160.
  • 7Steinwendner J, Schneider W, Suppan F. Vector segmentation using spatial subpixel analysis for object extraction. International Archives of Photogrammetry and Remote Sensing, 1998, 32: 265--271.
  • 8Atkinson PM. Super-resolution target mapping from soft-classi- fied remotely sensed imagery. In: Pullar DV, ed. Proceedings of the 6th International Conference on GeoComputation. Bris bane, Australia: GeoComputation CD-ROM, 2001.
  • 9Kasetkasema T, Arora MK, Varshney PK. Super-resolution land cover mapping using a Markov random field based approach. Remote Sensing of Environment, 2005, 96:302--314.
  • 10Mertens KC, Verbeke LPC, Ducheyne El, et al. Using genetic algorithms in sub-pixel mapping. International Journal of Remote Sensing, 2003, 24(21): 4241--4247.

共引文献18

同被引文献56

引证文献4

二级引证文献12

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部