Wyniki wyszukiwania - Biblioteka Nauki

1

Application of speckle decorrelation method for small translation measurements

100%

Horváth P. , Hrabovský M. , Šmíd P.

Optica Applicata

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2004

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tom Vol. 34, nr 2

203-218

EN

This paper analyses the usage of the speckle pattern decorrelation method for determination of small static and dynamic object translations. At first the philosophy of the method is presented briefly. Then relationships between the cross-correlation function and the small deformation tensor for the case of optically free space and image field are mentioned. Next, different experimental arrangements for the measurement of in-plane and normal object translations are analysed. Possible measurement ranges and sensitivities for each arrangement are discussed, too. Finally, some results of our experiments are shown

2

On Roughness Measurement by Angular Speckle Correlation

100%

Salazar F. , Belenguer T. , García J. , Ramos G.

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nr 2

3

On roughness measurement by angular speckle correlation

100%

Salazar F. , Belenguer T. , García J. , Ramos G.

Metrology and Measurement Systems

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2012

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tom Vol. 19, nr 2

373-380

EN

In this work, the influence of both characteristics of the lens and misalignment of the incident beams on roughness measurement is presented. To investigate how the focal length and diameter affect the degree of correlation between the speckle patterns, a set of experiments with different lenses is performed. On the other hand, the roughness when the beams separated by an amount are non-coincident at the same point on the sample is measured. To conclude the study, the uncertainty of the method is calculated.

4

Redukcja efektu plamkowania na obrazach radarowych z wykorzystaniem propagacyjno-separacyjnego algorytmu metody największej wiarygodności

89%

Kolecki J. , Badurska M.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2008

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tom Vol. 18a

251--261

PL

Redukcja szumów na obrazach jest istotnym etapem wstępnego przetwarzania danych. Zagadnienie redukcji szumów było wielokrotnie poruszane w licznych publikacjach naukowych. Przygotowanie danych przed wykonaniem właściwych analiz jest szczególnie ważne w przypadku obrazów radarowych, charakteryzujących się specyficznym szumem (tzw. speckle effect), który jest główną przeszkodą w interpretacji i klasyfikacji obrazów radarowych. Do redukcji tego typu szumów zaproponowano w pracy, opublikowaną w roku 2006 przez J. Polzehl i V. Spokoiny, nieparametryczną metodę opartą na stałym, lokalnym wygładzaniu z adaptacyjnym wyborem wag dla każdej pary punktów na obrazie (Adaptive Weights Smoothing – AWS). Algorytm AWS nie został do tej pory szczegółowo sprawdzony na obrazach radarowych. Zaproponowana metodyka stosowania algorytmu AWS polega na scaleniu w końcowy wynik przetworzenia trzech obrazów: obrazu oryginalnego i dwóch obrazów stanowiących rezultat działania algorytmu. Do badań wykorzystano zobrazowania wysokorozdzielczego satelity TerraSAR-X, testując rezultaty proponowanego podejścia na obrazach radarowych pozyskanych w różnych trybach, o różnej rozdzielczości i przedstawiających teren o różnym zagospodarowaniu (pola uprawne, obszar miejski). Rezultaty działania badanego algorytmu porównano z wynikami redukcji efektu plamkowania przy użyciu popularnych filtrów adaptacyjnych (filtru Lee i filtru Frost). Otrzymane wyniki potwierdzają przydatność algorytmu AWS jako efektywnego narzędzia redukującego charakterystyczne szumy radarowe.

EN

Solving the problem of image smoothing is regarded as an essential stage in preparing digital images for further processing. It was tackled by a number of studies. The presence of speckle noise in SAR images is the major obstacle in interpreting, classifying, and analyzing SAR images. The main problem in many remote sensing applications is the extraction and interpretation of information about the objects which are present on SAR images. This makes the speckle noise reduction a very important task. The reduction of speckles was performed by applying the nonparametric method, described by J. Polsehl and V. Spokoiny in 2006; the method is based on locally constant smoothing with an adaptive choice for every pair of data points (Adaptive Weights Smoothing – AWS). The AWS algorithm has never been tested in detail on SAR data. This paper describes the methodology of using the AWS algorithm by integrating three images: one original image and two images determining the result of the algorithm processed. The performance of the proposed method was tested on high-resolution X-band synthetic aperture radar TerraSAR-X images and was compared with popular adaptive filters (Lee, Frost). The method presented was tested on two samples extracted from images captured in different imaging modes, with different geometric resolution and showing various land use and land cover. The results confirm the utility of the propagation-separation approach for radar image smoothing.

5

Mechanical components dynamic characterization using thermoelastic stress analysis and digital image correlation

63%

Marsili R. , Rossi G.

Diagnostyka

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2018

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tom Vol. 19, No. 1

3--9

EN

In this work the possibility to characterize mechanical components combining thermoelastic measurement technique (TSA) and digital image correlation (DIC) is studied. The combination of these two different methodologies allows to analyze thermo-mechanical characteristics of materials such as plastic and rubber, which are difficult to study with the only thermoelastic methodology. The digital image correlation allows to determinate the first invariant of deformation ε1, using a differential thermocamera. Lack of adiabatic conditions, essential for methodology use, makes analysis not simple. Digital image correlation allows to obtain the same information by correlating digital images acquired during static or dynamic deformationof an object, but with limitations linked to acquisition system. An accurate analysis is dedicated to the study of first invariant of deformation related to Young’s module variation, performed by load cycles with variable amplitude and displacement. Comparative analysis between the two measurement methodologies has been performed on rubber samples loaded by dynamic compression.

6

Image Despeckling Based on LMMSE Wavelet Shrinkage

63%

Cui Y. , Zhang T. , Yu W.

Przegląd Elektrotechniczny

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2012

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tom R. 88, nr 7b

269--272

EN

A low complexity method for suppressing speckle in synthetic aperture radar (SAR) images is proposed. This method doesn’t require the logarithmic transform and is an extension of the linear minimum mean square error (LMMSE) filter to the image wavelet representation. A spatially adaptive shrinkage function is obtained and each modified coefficient is decided separately. Simulation results for the simulated SAR images demonstrate the proposed method outperforms some representative SAR despeckling methods.

PL

Zaproponowano metodę poprawy jakości obrazu w radarach typu SAR. Bazuje ona na liniowym minimum średniej kwadratu błędu LMMSE filtru. Wykorzystano adaptacyjną funkcję zbieżną w przestrzeni i wszystkie współczynniki modyfikowane są niezależnie.

7

Segmenting "flares" in ultrasound images using prior statistics

51%

Stippel G. , Duskunovic I. , Philips W. , Lemahieu I.

Image Processing & Communications

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2001

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tom Vol. 7, no 1-2

41-54

EN

The common method neonatologists use nowadays to determine White Matter Damage (leukomalacia) is by visual inspection of ultrasound images of the neonatal brain. A need for a (semi)-computerized computerized way of delineating the affected regions, in order to make quantitative measurements as an aid to the subjective diagnosis, is felt. The use of active contours for this purpose is a classical approach [5, 6]. The performance of active contours for this purpose, however, is heavily deteriorated by the presence of speckle noise. In this article a new filter, incorporating prior statistics concerning medical features in these images, is proposed, that removes a significant amount of speckle noise in the healthy parts, while it makes regions affected by WMD more uniform, thus severely improving the performance of the active contour. The results of the active contour after applying the proposed technique are compared with the manual delineation of an expert. Furthermore the proposed technique is compared with two other popular speckle suppression techniques, namely the ones proposed by Lee and Frost.