A gray consistency optical flow algorithmbased on mask-R-CNN and spatial filter forvelocity calculation

2021 ◽  
Author(s):  
Donghua Zhao ◽  
Yicheng Wu ◽  
Chenguang Wang ◽  
Chong Shen ◽  
Jun Tang ◽  
...  
Keyword(s):  
Optical Flow ◽  
Spatial Filter

Comparison of Deterministic and Linear Cosine Spatial Filtering of Transmission Electron Micrographs

1972 ◽  
Vol 30 ◽  
pp. 596-597
Author(s):  
David A. Ansley
Keyword(s):  
Spherical Aberration ◽  
Focal Length ◽  
Chromatic Aberration ◽  
Spatial Filter ◽  
Operating Conditions ◽  
Objective Lens ◽  
List Type ◽  
Spatial Filters ◽  
Transmission Electron ◽  
Wide Range

The coherence of the electron flux of a transmission electron microscope (TEM) limits the direct application of deconvolution techniques which have been used successfully on unmanned spacecraft programs. The theory assumes noncoherent illumination. Deconvolution of a TEM micrograph will, therefore, in general produce spurious detail rather than improved resolution.A primary goal of our research is to study the performance of several types of linear spatial filters as a function of specimen contrast, phase, and coherence. We have, therefore, developed a one-dimensional analysis and plotting program to simulate a wide 'range of operating conditions of the TEM, including adjustment of the:(1) Specimen amplitude, phase, and separation(2) Illumination wavelength, half-angle, and tilt(3) Objective lens focal length and aperture width(4) Spherical aberration, defocus, and chromatic aberration focus shift(5) Detector gamma, additive, and multiplicative noise constants(6) Type of spatial filter: linear cosine, linear sine, or deterministic

Optimum spatial filter for optical defocus sensing

1981 ◽  
Vol 64 (9) ◽  
pp. 113-120
Author(s):  
Kohji Takemura ◽  
Suteo Tsutsumi
Keyword(s):  
Spatial Filter ◽  
Optical Defocus

Motion correction in PET/CT

2005 ◽  
Vol 44 (S 01) ◽  
pp. S46-S50 ◽  
Author(s):  
M. Dawood ◽  
N. Lang ◽  
F. Büther ◽  
M. Schäfers ◽  
O. Schober ◽  
...  
Keyword(s):  
Optical Flow ◽  
Motion Correction ◽  
Motion Vector ◽  
Emission Tomography ◽  
Cardiac Pet ◽  
Novel Approach ◽  
Positron Emission ◽  
Pet Ct ◽  
Flow Algorithm ◽  
Motion Vector Field

Summary:Motion in PET/CT leads to artifacts in the reconstructed PET images due to the different acquisition times of positron emission tomography and computed tomography. The effect of motion on cardiac PET/CT images is evaluated in this study and a novel approach for motion correction based on optical flow methods is outlined. The Lukas-Kanade optical flow algorithm is used to calculate the motion vector field on both simulated phantom data as well as measured human PET data. The motion of the myocardium is corrected by non-linear registration techniques and results are compared to uncorrected images.

Locating Method for Vehicle at Intersection Based on TPVM and Optical Flow

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Tao Chen ◽  
Linkun Fan ◽  
Xuchuan Li ◽  
Congshuai Guo ◽  
Miaomiao Qiao
Keyword(s):  
Optical Flow

Wavelet-based Optical Flow Velocimetry (wOFV) Applied to Tagging Velocimetry Data

2021 ◽  
Author(s):  
Tobin Gevelber ◽  
Bryan E. Schmidt ◽  
Muhammad A. Mustafa ◽  
David Shekhtman ◽  
Nick J. Parziale
Keyword(s):  
Optical Flow ◽  
Flow Velocimetry
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