Hough变换在消除遥感图像随机相位相干干扰中的应用

doi:10.11873/j.issn.1004-0323.2001.1.55

遥感技术与应用

2001, Vol. 16

Issue (1): 55-62 DOI: 10.11873/j.issn.1004-0323.2001.1.55

技术方法

Hough变换在消除遥感图像随机相位相干干扰中的应用

全文: PDF

摘要： 郭　强,陈桂林,童卫旗(中国科学院上海技术物理研究所　上海　200083)摘要:遥感云图在气象、军事、生产生活等领域都有着广泛的应用。但是,由于在多通道扫描辐射计成像过程中部分子系统的影响,不可避免地在信号通道中耦合进一些相干干扰,这些干扰的存在将在一定程度上影响对遥感云图特征提取、目标识别等定量分析方法的有效性,因此必须将图像中的相干干扰予以消除或抑制。在对相干干扰特性进行分析并比较已有的几种消除方法的基础上,提出了基于二维频域分析的变换域Hough变换算法。实验表明,与邻域平均、中值滤波、经典频域滤波等消除干扰算法相比,该算法不仅能高质量地消除图像中的随机相位干干扰,同时还能有效地保留原图像中的细微影纹和边缘信息,并在航天遥感图像的实时采集及处理系统中获得成功应用。关　键　词:随机相位;相干干扰; Hough变换;二维频域分析中图分类号:TP 75

Abstract: An Application of the Hough Transform for Removingthe Random-phase Jam in the Remote Sensing ImageGUO Qiang, CHEN Gui-lin, Tong Wei-qi(Shanghai Insititute of Technical Physics,The Chinese Academy of Science,Shanghai200083China)Abstract:Remote Sensing Images have been applied extensively in the aspects of meteorology, militray andmanufacture. However, Because of the influences of some subsystems, a little correlation jam slip into thechannels inevitably during the imaging of the MCSR, which will damage the validities of the mensurableanalysis to the remote-sensing Images and the precise identification to the remote-sensing ground-objects inlager degrees. So the correlation jams must be removed or suppressed. Based on the analysis of the meritsof the correlation jam as well as comparision of several removel ways, the article presents the Hough trans-form algorithm upon the two-demension frenquency space analysis, its application in remote-sensing imageprocessing and its performances detailly. Experiental results show, compared with the methods of neigh-bour average, median filter and classical frenquency space filter, this algorithm is better in the removingrandom-phase jam of the images and reserves richer fine textures and edge information. On the otherhand, this algorithm makes it possible that the PSNRs of the processed images by this algorithm are higherthan the other removal ways above and the subjective evaluations to the processed images are better too.At the same time, this algorithm has also been applied to the real-time acquisition and processing of aus-tronautic remote sensing system and got the successful results.Key words:Random-phase, Correlation jam, Hough transform, Two-demension frenquency space analysis

出版日期: 2011-12-26

作者简介: 收稿日期:2000-10-20;修订日期:2000-12-15作者简介:郭强(1975-),男,博士生,从事图像实时处理和模式识别方面的研究工作。

	服务
	把本文推荐给朋友
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章

引用本文:

链接本文:

http://www.rsta.ac.cn/CN/Y2001/V16/I1/55

〔1〕　张幼文.红外光学工程〔M〕.上海:上海科学技术出版社,1981.〔2〕　Bo-Cai Cao. An Operational Method for Estimating Signal toNoise Ratios from Data Acquired with Imaging Spectrometers〔J〕.Remote Sens. Environ, 1993,43:23～33.〔3〕　王思贤,曾发龙.平滑图像噪声的插值滤波法〔J〕.电子科学学刊,2000,22(3):411～415〔4〕　Ballerd D H. Generalizing the Hough Transform of Detect Ar-bitrary Shape〔J〕. Pattern Recognition,1981,13(2):111～112.〔5〕　张元,汪庆宝,方惠明.数字信号处理〔M〕.北京:北京工业大学出版社,1995.

No related articles found!

Viewed

Full text

Abstract

Cited

Shared

Discussed