基于局部维纳滤波的交通图像去雾霾算法.docx

基于局部维纳滤波的交通图像去雾霾算法
摘要
路面交通安全是社会生活中不可缺少的一部分，而雾霾天气则对交通流造成了严重的影响。本文提出了一种基于局部维纳滤波的交通图像去雾霾算法，以提升交通图像的清晰度和可见度。该算法采用了一种局部维纳滤波和雾霾模型，通过对图像进行去雾霾处理，同时保留图像的细节和颜色信息。在实验中，我们使用了具有不同雾霾程度的交通图像，结果说明该算法能够有效地改善图像的质量，并提高其可见度。
关键词：局部维纳滤波；雾霾模型；交通图像
Abstract
Roadtrafficsafetyisanindispensablepartofsociallife,whilehazeweatherhasaseriousimpactontrafficflow.Inthispaper,atrafficimagedehazingalgorithmbasedonlocalWienerfilteringisproposedtoimprovetheclarityandvisibilityoftrafficimages.ThisalgorithmusesalocalWienerfilterandhazemodeltodehazetheimagewhilepreservingthedetailsandcolorinformationoftheimage.Intheexperiment,trafficimageswithdifferentlevelsofhazewereused,andtheresultsshowedthatthealgorithmcaneffectivelyimprovethequalityoftheimageandincreaseitsvisibility.
Keywords:LocalWienerfilter;Hazemodel;Trafficimage
1.Introduction
Hazeweatherhasbecomeamajorenvironmentalprobleminrecentyearsinmanyregionsandhasaffectedmanyaspectsofdailylife,includingtransportation.Duringhazeweather,thevisibilityoftrafficimagesdecreasessignificantly,whichcancauseserioustrafficaccidents.Therefore,itisnecessarytoimprovetheclarityandvisibilityoftrafficimagesinhazeweather.
Inrecentyears,manymethodshavebeenproposedtoimprovethequalityoftrafficimagesinhazeweather,suchasdarkchannelprioralgorithmandatmosphericscatteringmodelalgorithm.However,thesealgorithmshavesomelimitationsinpractice,suchaspoorperformanceinareaswithdifferentlightsourcesandinabilitytorestoreaccuratecolorinformation.Inaddition,thesemethodsusuallyrequirealargeamountofcomputationandaretime-consuming.
Inthispaper,weproposeatrafficimagedehazingalgorithmbasedonlocalWienerfiltering.ThisalgorithmusesalocalWienerfilterandhazemodeltodehazetheimagewhilepreservingthedetailsandcolorinformationoftheimage.Therestofthepaperisorganizedasfollows:section2presentsrelatedwork,section3introducestheproposedalgorithm,section4showsexperimentresults,andsection5concludesthepaperwithfuturework.
2.Relatedwork
Manymethodshavebeenproposedtoimprovethequalityoftrafficimagesinhazeweather,suchasd