數(shù)字圖像處理中英文對(duì)照外文翻譯文獻(xiàn)

1、 (文檔含英文原文和中文翻譯)中英文翻譯原 文To image edge examination algorithm researchAbstract ：Digital image processing took a relative quite young discipline,is following the computer technology rapid development, day by day obtains thewidespread application.The edge took the image one kind of basic characteristic,i

2、n the pattern recognition, the image division, the image intensification aswell as the image compression and so on in the domain has a more widespreadapplication.Image edge detection method many and varied, in which based on第 1 頁(yè) brightness algorithm, is studies the time to be most long, the theory

3、developsthe maturest method, it mainly is through some difference operator, calculatesits gradient based on image brightness the change, thus examines the edge, mainlyhas Robert, Laplacian, Sobel, Canny, operators and so on LOG。First as a whole introduced digital image processing and the edge detect

4、ionsurvey, has enumerated several kind of at present commonly used edge detectiontechnology and the algorithm, and selects two kinds to use Visual the C languageprogramming realization, through withdraws the image result to two algorithmsthe comparison, the research discusses their good and bad poin

5、ts.Foreword：In image processing, as a basic characteristic, the edge oftheimage, which is widely used in the recognition, segmentation,intensificationand compress of the image, is often applied tohigh-level domain.There are manykinds of ways to detect the edge. Anyway, there aretwo main techniques:

6、one isclassic method based on the gray grade ofevery pixel; the other one is basedon wavelet and its multi-scalecharacteristic. The first method, which is gotthe longest research,get the edge according to the variety of the pixel gray.The maintechniques are Robert, Laplace, Sobel, Canny and LOG algo

7、rithm.The second method, which is based on wavelet transform, utilizestheLipschitz exponent characterization of the noise and singular signaland thenachieve the goal of removing noise and distilling the realedge lines. In recentyears, a new kind of detection method, which basedon the phase informati

8、on ofthe pixel, is developed. We need hypothesizenothing about images in advance.The edge is easy to find in frequencydomain. Its a reliable method.In chapter one, we give an overview of the image edge. And inchapter two,some classic detection algorithms are introduced. Thecause of positional errori

9、s analyzed, and then discussed a moreprecision method in edge orientation. Inchapter three, wavelet theoryis introduced. The detection methods based onsampling wavelettransform, which can extract maim edge of the image effectively,andnon-sampling wavelet transform, which can remain the optimumspatia

10、linformation, are recommended respectively. In the last chapter ofthisthesis, the algorithm based on phase information is introduced. Usingthe第 2 頁(yè) log Gabor wavelet, two-dimension filter is constructed, many kindsof edges aredetected, including Mach Band, which indicates it is aoutstanding andbio-s

11、imulation method。May all the work in this paper is of some value to researchand applications of image edge detection.First chapter introduction1.1 image edge examination introductionThe image edge is one of image most basic characteristics, often is carryingimage majority of informations。But the edg

12、e exists in the image irregularstructure and in not the steady phenomenon, also namely exists in the signalpoint of discontinuity place,these spots have given the imageoutline position, these outlinesare frequently we when theimagery processing needs theextremelyimportantsomerepresentative condition

13、, thisneeds us to examine and towithdraw its edge to an image。Buttheedgeexaminationalgorithm is in the imageryprocessing question one of classical technical difficult problems, its solutioncarries on the high level regarding us the characteristic description, therecognition and the understanding and

14、 so on has the significant influence; Alsobecause the edge examination all has in many aspects the extremely importantuse value, therefore how the people are devoting continuously in study and solvethe structure to leave have the good nature and the good effect edge examinationoperator question。In t

15、he usual situation, we may the signal in singular pointand the point of discontinuity thought is in the image peripheral point, itsnearby gradation change situation may reflect from its neighboring pictureelement gradation distribution gradient。According to this characteristic, we proposed many kind

16、s of edge examination第 3 頁(yè) operator: If Robert operator, Sobel operator, Prewitt operator, Laplace operatorand so on.These methods many are wait for the processing picture element to carryon the gradation analysis for the central neighborhood achievement thefoundation, realized and has already obtai

17、ned the good processing effect to theimage edge extraction.。But this kind of method simultaneously also exists hasthe edge picture element width, the noise jamming is serious and so on theshortcomings, even if uses some auxiliary methods to perform the denoising, alsocorresponding can bring the flaw

18、 which the edge fuzzy and so on overcomes withdifficulty。Along with the wavelet analysis appearance， its good time frequencypartial characteristic by the widespread application in the imagery processingand in the pattern recognition domain, becomes in the signal processing thecommonly used method an

19、d the powerful tool。Through the wavelet analysis, mayinterweave decomposes in the same place each kind of composite signal thedifferent frequency the block signal ， but carries on the edge examinationthrough the wavelet transformation, may use its multi-criteria and themulti-resolution nature fully，

20、 real effective expresses the image the edgecharacteristic。When the wavelet transformation criterion reduces, is moresensitive to the image detail; But when the criterion increases, the image detailis filtered out, the examination edge will be only the thick outline.Thischaracteristic is extremely u

21、seful in the pattern recognition, we may be calledthis thick outline the image the main edge.If will be able an image main edgeclear integrity extraction, this to the goal division, the recognition and soon following processing to bring the enormous convenience.Generally speaking,the above method al

22、l is the work which does based on the image luminanceinformation。In the multitudinous scientific research worker under, has obtained the verygood effect diligently.But, because the image edge receives physical conditionand so on the illumination influences quite to be big above, often enables manyto

23、haveacommonbased onshortcomingbrightness edge detection method, that is the edge is not continual, does not seal up.Considered the phaseinformation in the image importance as well as its stable characteristic, causesusing the phase information to carry on the imagery processing into new researchtopi

24、c。In this paper soon introduces one kind based on the phase imagecharacteristic examination method - - phase uniform method.It is not uses theimage the luminance information, but is its phase characteristic, namelysupposition image Fourier component phase most consistent spot achievementcharacterist

25、ic point.Not only it can examine brightness characteristics and soon step characteristic, line characteristic, moreover can examine Mach beltphenomenon which produces as a result of the human vision sensationcharacteristic.Because the phase uniformity does not need to carry on anysupposition to the

26、image characteristic type, therefore it has the very strongversatility。1.2 image edge definitionThe image majority main information all exists in the image edge, the mainperformance for the image partial characteristic discontinuity, is in the imagethe gradation change quite fierce place, also is th

27、e signal which we usuallysaid has the strange change place。The strange signal the gradation change whichmoves towards along the edge is fierce, usually we divide the edge for the stepshape and the roof shape two kind of types (as shown in Figure 1-1).In the stepedge two side grey levels have the obv

28、ious change; But the roof shape edge islocated the gradation increase and the reduced intersection point.May portraythe peripheral point in mathematics using the gradation derivative the change,to the step edge,the roof shape edge asks its step, thesecond time derivativeseparately。To an edge, has th

29、e possibility simultaneously to have the step and the lineedge characteristic. For example on a surface, changes from a plane to the normaldirection different another plane can produce the step edge; If this surfacehas the edges and corners which the regular reflection characteristic also twoplanes

30、form quite to be smooth, then works as when edges and corners smooth第 5 頁(yè) surface normal after mirror surface reflection angle, as a result of the regularreflection component, can produce the bright light strip on the edges and cornerssmooth surface, such edge looked like has likely superimposed a l

31、ine edge inthe step edge. Because edge possible and in scene object important characteristiccorrespondence, therefore it is the very important image characteristic。Forinstance, an object outline usually produces the step edge, because the objectimage intensity is different with the background image

32、intensity。1.3 paper selected topic theory significanceThe paper selected topic originates in holds the important status andthe function practical application topic in the image project.The so-calledimage project discipline is refers foundation discipline and so on mathematics,optics principles, the

33、discipline which in the imageapplication unifies whichaccumulates the technical background develops.The image project content isextremely rich, and so on divides into three levels differently according tothe abstract degree and the research technique: Imagery processing, imageanalysis and image unde

34、rstanding。As shown in Figure 1-2, in the chart, the imagedivision is in between the image analysis and the imagery processing, its meaningis, the image division is from the imagery processing to the image analysisessential step, also is further understands the image the foundation。The image division

35、 has the important influence to the characteristic.Theimage division and based on the division goal expression, the characteristicextraction and the parameter survey and so on transforms the primitive imageas a more abstract more compact form, causes the high-level image analysis andpossibly underst

36、ands into.But the edge examination is the image division corecontent, therefore the edge examination holds the important status and thefunction in the image project.Therefore the edge examination research alwaysis in the image engineering research the hot spot and the focal point, moreoverthe people

37、 enhance unceasingly to its attention and the investment。1.4 this article prime tasks1.4.1 Algorithm content第 6 頁(yè) Introduced and has analyzed the classics image edge examination algorithm,summarized each algorithm good and bad points, has given the image edgeexamination result, and emphatically take

38、 the LOG algorithm as the example,embarked from the noise and the edge shape viewpoint has analyzed the reasonwhich the edge position error produced; Introduced in one kind of LOG algorithmthe quite precise definite edge method。1.4.2 Wavelet theoryHas studied the wavelet elementary theory, summarize

39、d the signal as wellas the noise Lip index nature, and in based on in the non-sampling wavelettransformation image characteristic extraction algorithm foundation, unifiesthe auto-adapted denoising method, has made certain improvement to this method,obtained the quite satisfactory effect, denoising a

40、bility had the quite bigenhancement; Then introduced one kind based on the sampling wavelet examinationimage main edge method。1.4.3 Novel algorithmThe system has studied one kind quite novel based on the phase imagecharacteristic extraction algorithm - phase uniform algorithm,and has givenits simple

41、 algorithm.Has given in the unidimensional situation algorithmsimulation step, analyzed expanded to the two-dimensional method, and explainedby the edge examination result the phase uniform algorithm conformed to the humanvision characteristic。1.5 this article content arrangementIn the first chapter

42、, the author has given an outline explanation to theimage edge examination, and explained carries on the image edge examination thevital significance.In second chapter, the system introduced the quite classicalimage edge examination operator and the concrete realization principle, haveanalyzed each

43、algorithm existence insufficiency by the edge examinationresult.Finally, from the noise influence and edge shape obtaining, take the LOGalgorithm as the example, has analyzed the reason which the false edge as wellas edge shifting produces.Finally introduced in one kind of LOG algorithm thequite pre

44、cise definite edge method.第 7 頁(yè) In third chapter, the author system introduced the present quite popularwavelet theory, and introduced emphatically the multi-criterion concept and thesignal Lip index, and by the noise and the signal Lip index characteristic,carries on the extraction in the non-sampl

45、ing wavelet transformation foundationto the image edge.In order to strengthen the edge image anti-chirp ability, butalso the algorithm has made certain improvement regarding this, the auto-adapteddenoising method will use in the edge detection, has obtained the satisfyingeffect.Finally also introduc

46、es one kind based on the sampling waveletexamination image main edge method.In the this article fourth chapter,introduced one kind quite novel based on the phase image characteristicextraction algorithm - - phase uniform algorithm.From unidimensional algorithmintroduction obtaining, has given under

47、the unidimensional signal simulationresult, and expands gradually two-dimensionally.Explained through thesimulation result this algorithm robustness quite is strong, moreover conformsto humanitys visual system performance.Second chapter classical image edge examination algorithmThis chapter first si

48、mply introduced a classics step edge examinationessential method in 2.1.Then 2.2 and 2.3 distinctions elaborated specificallythe classical derivative operator and the linear filtering operator realizationmethod, and has given each algorithm result comparison in 2.4.In 2.5, comparedwith the concrete

49、analysis noise and the edge shape the reason which producedto the edge pointing accuracy influence as well as the false edge, and has givenin the unidimensional situation simulation result, has drawn the conclusion.In2.6, the image positive and negative edge which picks out using the LOG algorithm,c

50、ompared with the precise localization image real edge, the final output wastwo value single picture element image.2.1 classical edge examination essential methodWe knew that, the edge examination essence is uses some algorithm to withdrawin the image the object and the background junction demarcatio

51、n line.We definethe edge for the image in the gradation occur the rapid change region boundary.Theimage gradation change situation may use the image gradation distribution the第 8 頁(yè) gradient to reflect, therefore we may use the partial image differentialtechnology to obtain the edge examination opera

52、tor.The edge examination algorithm has the following four steps ( its process asshown in Figure2-1):Filter: The edge examination algorithm mainly is based on an image intensitystep and the second time derivative, but the derivative computation is verysensitive to the noise, therefore must use the fi

53、lter to improve and the noiserelated edge detector performance.Needs to point out that,the majority filterhave also caused the edge intensity loss while noise reduction, therefore,strengthens the edge and between the noise reduction needs compromised.Enhancement: Strengthens the edge the foundation

54、is determines the imageeach neighborhood intensity the change value.The enhancement algorithm may (orpartial) the intensity value has the neighborhood the remarkable change spotto reveal suddenly.The edge strengthens is generally completes through thecomputation gradient peak-to-peak value.Examinati

55、on: Has many point gradient peak-to-peak value in the image quiteto be big, but these in the specific application domain not all is the edge,therefore should use some method to determine which select is the peripheralpoints.The simple edge examination criterion is the gradient peak-to-peak valuethre

56、shold value criterion.Localization: If some application situation request definite edge position,then the edge position may come up the estimate in the sub-picture elementresolution, the edge position also may estimate.In the edge examinationalgorithm, the first three steps use extremely universally

57、.This is because underthe majority situations, needs the edge detector to point out merely the edgeappears in image some picture element neighbor, but is not unnecessary to pointout the edge the exact location or the direction.The edge examines the error usually is refers to the edge to classify the

58、error by mistake, namely distinguished the vacation edge the edge retains, butdistinguished the real edge the vacation edge removes.The edge error ofestimation is describes the edge position and the lateral error with the第 9 頁(yè) probability statistical model.We examine the edge the error and the edge

59、errorof estimation differentiate, is because their computational method is completelydifferent, its error model completely is also different.The edge examination is examines the image partial remarkable change themost fundamental operation. In the unidimensional situation, the step edgeconcerns with

60、 the image first derivative partial peak value. The gradient isthe function change one kind of measure, but an image may regard as is the imageintensity continuous function sampling point array. Therefore, is similar withthe unidimensional situation, the image grey level remarkable change availableg