Fourier Integral Representation of an Optical Image

2009 ◽  
pp. 23-43
Keyword(s):  
Integral Representation ◽  
Fourier Integral ◽  
Optical Image

Fourier integral representation of the Green function for an anisotropic elastic half-space

1993 ◽  
Vol 443 (1918) ◽  
pp. 367-389 ◽  
Keyword(s):  
Green Function ◽  
Integral Representation ◽  
Half Space ◽  
Isotropic Material ◽  
Fourier Integral ◽  
Elastic Half Space ◽  
Material Symmetry ◽  
Vertical Force ◽  
Anisotropic Elastic ◽  
The Green Function

This paper describes the development of a Fourier integral representation of the Green function for an anisotropic elastic half-space. The representation for an isotropic material is integrated in closed form and shown to reduce to Mindlin’s solution. An application of the anisotropic representation is made to deduce the exact displacement caused by a two-dimensional periodic vertical force distribu­tion applied to the interior of a half-space with cubic material symmetry.

Registration and Fusion of UAV LiDAR System Sequence Images and Laser Point Clouds

2020 ◽  
Author(s):  
Jiayong Yu ◽  
Longchen Ma ◽  
Maoyi Tian, ◽  
Xiushan Lu
Keyword(s):  
Point Cloud ◽  
Image Data ◽  
Point Clouds ◽  
Optical Image ◽  
Point Cloud Data ◽  
Feature Points ◽  
Lidar System ◽  
Registration Accuracy ◽  
Cloud Data ◽  
Intensity Image

The unmanned aerial vehicle (UAV)-mounted mobile LiDAR system (ULS) is widely used for geomatics owing to its efficient data acquisition and convenient operation. However, due to limited carrying capacity of a UAV, sensors integrated in the ULS should be small and lightweight, which results in decrease in the density of the collected scanning points. This affects registration between image data and point cloud data. To address this issue, the authors propose a method for registering and fusing ULS sequence images and laser point clouds, wherein they convert the problem of registering point cloud data and image data into a problem of matching feature points between the two images. First, a point cloud is selected to produce an intensity image. Subsequently, the corresponding feature points of the intensity image and the optical image are matched, and exterior orientation parameters are solved using a collinear equation based on image position and orientation. Finally, the sequence images are fused with the laser point cloud, based on the Global Navigation Satellite System (GNSS) time index of the optical image, to generate a true color point cloud. The experimental results show the higher registration accuracy and fusion speed of the proposed method, thereby demonstrating its accuracy and effectiveness.

VIS-NIR LED Illumination in Backside Circuit Edit and Optical Probing Applications

2012 ◽  
Author(s):  
Shida Tan ◽  
Richard H. Livengood ◽  
Dane Scott ◽  
Roy Hallstein ◽  
Pat Pardy ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Optical Imaging ◽  
Narrow Band ◽  
Light Emitting Diode ◽  
Air Gap ◽  
Optical Image ◽  
Proof Of Concept ◽  
Light Emitting ◽  
Optical Probing

Abstract High resolution optical imaging is critical in assisting backside circuit edit (CE) and optical probing navigation. In this paper, we demonstrated improved optical image quality using VIS-NIR narrow band light emitting diode (LED) illumination in various FIB and optical probing platforms. The proof of concept was demonstrated with both common non-contact air gap lenses and solid immersion lenses (SIL).

Fourier Integral Methods of Pattern Analysis

1946 ◽  
Author(s):  
MASSACHUSETTS INST OF TECH CAMBRIDGE
Keyword(s):  
Pattern Analysis ◽  
Fourier Integral ◽  
Integral Methods
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