遥感技术与应用
遙感技術與應用
요감기술여응용
REMOTE SENSING TECHNOLOGY AND APPLICATION
2001年
1期
55-61
,共7页
随机相位%相干干扰%Hough变换%二维频域分析
隨機相位%相榦榦擾%Hough變換%二維頻域分析
수궤상위%상간간우%Hough변환%이유빈역분석
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。
遙感雲圖在氣象、軍事、生產生活等領域都有著廣汎的應用。但是,由于在多通道掃描輻射計成像過程中部分子繫統的影響,不可避免地在信號通道中耦閤進一些相榦榦擾,這些榦擾的存在將在一定程度上影響對遙感雲圖特徵提取、目標識彆等定量分析方法的有效性,因此必鬚將圖像中的相榦榦擾予以消除或抑製。在對相榦榦擾特性進行分析併比較已有的幾種消除方法的基礎上,提齣瞭基于二維頻域分析的變換域Hough變換算法。實驗錶明,與鄰域平均、中值濾波、經典頻域濾波等消除榦擾算法相比,該算法不僅能高質量地消除圖像中的隨機相位榦榦擾,同時還能有效地保留原圖像中的細微影紋和邊緣信息,併在航天遙感圖像的實時採集及處理繫統中穫得成功應用。
요감운도재기상、군사、생산생활등영역도유착엄범적응용。단시,유우재다통도소묘복사계성상과정중부분자계통적영향,불가피면지재신호통도중우합진일사상간간우,저사간우적존재장재일정정도상영향대요감운도특정제취、목표식별등정량분석방법적유효성,인차필수장도상중적상간간우여이소제혹억제。재대상간간우특성진행분석병비교이유적궤충소제방법적기출상,제출료기우이유빈역분석적변환역Hough변환산법。실험표명,여린역평균、중치려파、경전빈역려파등소제간우산법상비,해산법불부능고질량지소제도상중적수궤상위간간우,동시환능유효지보류원도상중적세미영문화변연신식,병재항천요감도상적실시채집급처리계통중획득성공응용。
Remote Sensing Images have been applied extensively in theaspects of meteorology, militray and manufacture. However, Because of the influences of some subsystems, a little correlation jam slip into the channels inevitably during the imaging of the MCSR, which will damage the validities of the mensurable analysis to the remote-sensing Images and the precise identification to the remote-sensing ground-objects in lager degrees. So the correlation jams must be removed or suppressed. Based on the analysis of the merits of the correlation jam as well as comparision of several removel ways, the article presents the Hough transform algorithm upon the two-demension frenquency space analysis, its application in remote-sensing image processing and its performances detailly. Experiental results show, compared with the methods of neighbour average, median filter and classical frenquency space filter, this algorithm is better in the removing random-phase jam of the images and reserves richer fine textures and edge information. On the other hand, this algorithm makes it possible that the PSNRs of the processed images by this algorithm are higher than 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 austronautic remote sensing system and got the successful results.