scholarly journals Sparse spatial filter via a novel objective function minimization with smooth ℓ1 regularization

2013 ◽  
Vol 8 (3) ◽  
pp. 282-288 ◽  
Author(s):  
Ibrahim Onaran ◽  
N. Firat Ince ◽  
A. Enis Cetin
Keyword(s):  
Objective Function ◽  
Spatial Filter ◽  
Function Minimization ◽  
ℓ1 Regularization

A New Image Demising Method Based on Partial Differential Equations

2013 ◽  
Vol 443 ◽  
pp. 22-26
Author(s):  
Yong Xing Lin ◽  
Xiao Yan Xu ◽  
Xian Dong Zhang
Keyword(s):  
Image Processing ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Diffusion Equation ◽  
Objective Function ◽  
Thermal Diffusion ◽  
Minimization Problem ◽  
Iterative Process ◽  
Function Minimization ◽  
Partial Differential

In the paper, we discuss the image demising models, based on partial differential equations. It is through the use of the concept of variations in the calculus of the objective function minimization problem, defines the image processing tasks. The results show that the model expands 2d thermal diffusion equation. Therefore, it is easy to get solution is to use a simple iterative process.

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
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