Wyniki wyszukiwania - Biblioteka Nauki

1

Valorization of the noise content in photogrammetric images using wavelets

100%

Pyka K.

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tom Vol. 2, no. 1

59-65

EN

In the paper the use of wavelet transformation for valorization of noise content in photogrammetric images is proposed. At first noise in the digital images and applied methods of noise removing is described synthetically. Then the most important features of wavelet transformation are presented through the comparison with Fourier transformation, widely used in the similar problems. Valorization of the noise content was based on the observation given in literature, stating that the noise changes the shape of the transform detail components histograms. The fragments of aerial photographs and high-resolution satellite images were used as a research material. The researches confirmed the possibility to define the noise content indicators based on the analysis of the wavelet detail coefficients distribution shape. It was found that investigation of the wavelet components histograms shape can be employed for the comparison of the radiometric changes occurred during radiometric and geometric processing of the images.

PL

W pracy zaproponowano zastosowanie transformacji falkowej do waloryzacji zawartości szumów losowych występujących w obrazach fotogrametrycznych. Najpierw omówiono syntetycznie problem szumów w obrazach cyfrowych oraz stosowane metody ich usuwania. Następnie przedstawiono najważniejsze cechy transformacji falkowej, poprzez porównanie do powszechnie stosowanej - w podobnych zagadnieniach - transformacji Fouriera. Waloryzacje zawartości szumów oparto na podanych w literaturze spostrzeżeniach, że szum zmienia kształt histogramów komponentów detalicznych transformaty falkowej. Jako materiał badawczy wykorzystano fragmenty zdjęć lotniczych i wysokorozdzielczych obrazów satelitarnych. Badania potwierdziły możliwość formułowania wskaźników zawartości szumów, opartych na analizie kształtu rozkładów współczynników detali falkowych. Stwierdzono, że badanie kształtu histogramów komponentów falkowych może być zastosowane do porównywania zmian radiometrycznych następujących podczas radiometrycznego i geometrycznego przetwarzania obrazów.

2

Czy kurtoza mierzy spiczastość rozkładu?

84%

Kochanski B.

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tom 67

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nr 11

3

The investigation of the optimization scheme of the low‑cycle fatigue cropping based on the acoustic emission technique

67%

Ren Y. , Li J. , Dong Y. , Zhao S. , Liu B. , Jin D.

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2022

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tom Vol. 22, no. 2

art. no. e61, 1--15

EN

Low-cycle fatigue cropping (LCFC) is a new metal bar separation method which utilizes the material fracture under cyclic load. To achieve good and fast separation of metal bars, a control scheme based on characteristics of whole cropping process is necessary. Three kinds of materials, such as 16Mn, 1045 and Al 6061, have been operated in this study and found that the kurtosis is more suitable as a monitoring parameter in control method, because it has a better stability in the complicated industrial environment. In addition, crack instability stage formed the most uneven region on the section and the best time when change the frequency is before crack instability stage. According to the above results, an optimal control scheme which by reducing the loading frequency before the crack instability stage based on the acoustic emission kurtosis is proposed. Moreover, four control strategies’ results for three kinds of materials are compared, and find the section quality increases with the decrease of loading frequency, but the effect of this increase decreases with the decrease of loading frequency. To evaluate the advantages and disadvantages of the control strategy, a parameter combining efficiency and section quality is proposed, and according to this parameter, the most suitable control strategy for three materials is obtained.

4

Formulation and statistical evaluation of an automated algorithm for locating small bowel tumours in wireless capsule endoscopy

67%

Jagadeesan A. , Sivaraman J.

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tom Vol. 38, no. 4

782--793

EN

Wireless capsule endoscopy (WCE) is an imaging modality which is highly reliable in the diagnosis of small bowel tumors. But locating the frames carrying tumors manually from the lengthy WCE is cumbersome and time consuming. A simple algorithm for the automated detection of tumorous frames from WCE is proposed in this work. In the proposed algorithm, local binary pattern (LBP) of the contrast enhanced green channel is used as the textural descriptor of the WCE frames. The features employed to differentiate tumorous and nontumorous frames are skewness (S) and kurtosis (K) of the LBP histogram. The threshold value of the features which offers the trade-off between sensitivity and specificity is identified through Receiver Operating Characteristic (ROC) curve analysis. At the optimum threshold, both the features exhibited a sensitivity of 100% and specificity of 90%. The skewness and kurtosis of the LBP computed from the enhanced green channel of tumorous and nontumorous frames differ significantly ( p « 0.05) with a p-value of 2.2 x 10-16. The proposed method is helpful to reduce the time spent by the doctors for reviewing WCE.