计算机科学 ›› 2016, Vol. 43 ›› Issue (2): 38-40.doi: 10.11896/j.issn.1002-137X.2016.02.008

• 2015年中国计算机学会人工智能会议 • 上一篇    下一篇

组合粗尺度异质性和细尺度匀质性的像元交换算法用于超分辨率制图

胡建龙,李德玉,白鹤祥   

  1. 山西大学计算机与信息技术学院 太原030006,山西大学计算机与信息技术学院 太原030006;山西大学计算智能与中文信息处理教育部重点实验室 太原030006,山西大学计算机与信息技术学院 太原030006
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(61272095),山西省自然科学基金(2013011066-4),山西省回国留学人员重点科研资助

Super-resolution Mapping Using Pixel-swapping Based on Integration of Coarse-scale Spatial Heterogeneity and Fine-scale Spatial Homogeneity

HU Jian-long, LI De-yu and BAI He-xiang   

  • Online:2018-12-01 Published:2018-12-01

摘要: 空间依赖性的刻画对超分辨率制图方法起着关键作用。根据观察及实验,粗尺度空间能更好地刻画空间地物异质性,同时细尺度空间能更好地刻画空间地物的匀质性。因此提出了一种结合粗尺度空间异质性和细尺度空间匀质性的像元交换算法用于超分辨率制图。提出的基于组合粗尺度异质性和细尺度匀质性的空间依赖性度量能更好地刻画复杂地物环境。在合成影像上的实验结果验证了提出的算法能在保持分数信息不变的前提下获得更高的制图精度。

关键词: 匀质性,异质性,超分辨率制图

Abstract: Spatial dependence characterization plays a key role for super-resolution mapping.Experiments and observations show that the coarse-scale spatial heterogeneity characterization can better describe spatital heterogeneity of ground objects between different classes,while the fine-scale spatial homogeneity characterization can better describe spatital homogeneity of ground objects in the same class.This paper proposed a new algorithm for super-resolution mapping using pixel-swapping strategy based on the combination of spatial heterogeneity at coarse scale and homogeneity at fine scale.The integration of coarse-scale heterogeneity and fine-scale homogeneity will better represent features of complex land cover.Experimental results on the sythentic image further validate the effectiveness of algorithm and it achieves higher precision under the premise of the same fraction information.

Key words: Homogeneity,Heterogeneity,Super-resolution mapping

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