scholarly journals METHOD FOR ADDING HIGH FREQUENCY COMPONENTS TO A VELOCITY FIELD OBTAINED FROM A MESOSCALE METEOROLOGICAL MODEL

2020 ◽  
Vol 85 (767) ◽  
pp. 19-27
Author(s):  
Hidenori KAWAI ◽  
Tetsuro TAMURA
Keyword(s):  
Velocity Field ◽  
High Frequency ◽  
Meteorological Model ◽  
Mesoscale Meteorological Model ◽  
Frequency Components

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

Проблемы локации источников акустической эмиссии

2021 ◽  
pp. 35-44
Author(s):  
Ю.Г. Матвиенко ◽  
И.Е. Васильев ◽  
Д.В. Чернов ◽  
В.И. Иванов ◽  
С.В. Елизаров
Keyword(s):  
Acoustic Emission ◽  
High Frequency ◽  
Tensile Tests ◽  
Threshold Method ◽  
Near Zone ◽  
Speed Dependence ◽  
Partial Energy ◽  
Base Size ◽  
Frequency Components ◽  
Amplitude Level

The accuracy of the location of acoustic emission (AE) sources in the concentrator zones (central holes 5 mm in diameter) located at a distance of 40 mm from the receiving transducers during tensile tests of steel, aluminum alloy and composite flat specimens with dimensions of 550x50x4 mm was evaluated. Calculated speed dependence of propagation of pulses on the level of their amplitude and the partial energy of the high-frequency components of the spectrum is studied. With the threshold method of signal registration, the error in the location of AE event sources arising in the near zone of the receiving transducers at a distance 𝛥L<0.1 m can significantly exceed 10% relative to the base size (B) of the location area, when B<0.5 m. Moreover, with a decrease in the distance 𝛥L<0.05 m, the level of possible error will increase, reaching 20-30% relative to the basic size of the antenna array, when recording pulses with an amplitude level um<60 dB and a fraction of the energy of high-frequency spectrum components not exceeding 10%.

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