基于卡尔曼滤波的光学遥感影像高精度复原处理
High Precision Image Restoration Based on Kalman Filter for Optical Remote Sensed Images
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摘要: 光学卫星成像系统调制传递函数(MTF)的准确量测是高质量影像复原的基础。传统的MTF测量方法忽略了卫星平台振动、影像噪声等因素的干扰,导致测量结果与真实值存在较大偏差,不利于影像质量的提升。本文在分析现有MTF测量方法的基础上,提出了基于卡尔曼滤波的高精度MTF测量方法,该方法利用卡尔曼滤波对实测的线扩展函数(LSF)进行迭代处理,获取无干扰的LSF,为影像复原质量的提高奠定基础。本文利用国产高分辨率卫星成像数据进行实验,采用边缘能量、对比度、奈奎斯特频率值作为复原前后影像质量评价的依据,实验结果表明,采用本文方法获取的MTF进行复原的影像无论是在边缘保持还是噪声抑制方面都优于传统方法。Abstract: HighprecisionMTFmeasurementisthebasisofhighqualityimagerestoration.Giventhepresenceofnoiseinimagesandvibrationfromthepayload,traditionalMTFmeasurementbasedonthetargetimagewillproduceabiasedresult,andthebiasedresultwillintroducenewnoiseafterim agerestoration.Inthispaper,basedonanalysisofcharacteristicsandlimitationsoftraditionalimagerestorationmethod,weproposeanimagerestorationapproachbasedonhighprecisionMTFmeasure mentusingtheKalmanfilter.ThisapproachfirstlyusesGuassianfittingtoobtaintheoreticalvalueofthelinespreadfunctionfromthemeasuredvalue,thenitusestheKalmanfiltertoobtainthetrueval ueofthelinespreadfunctionfromtheoreticalvalueandmeasuredvalue.ExperimentsonTDI CCDimagesshowthattheapproachproposedinthispaperyieldbetterperformancethantraditionalimagerestoration,especiallyforthewaterareaswhichcontainlesstextureandcityareaswhichcontainsrichtexture.
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