Principles and applications of time-encoded single-pixel imaging technology (Conference Presentation)

2019 ◽  
Author(s):  
Hongwei Chen
Keyword(s):  
Imaging Technology ◽  
Single Pixel

scholarly journals Non-Scanning Three-Dimensional Imaging System with a Single-Pixel Detector: Simulation and Experimental Study

2020 ◽  
Vol 10 (9) ◽  
pp. 3100
Author(s):  
Guang Shi ◽  
Leijue Zheng ◽  
Wen Wang ◽  
Keqing Lu
Keyword(s):  
3D Imaging ◽  
Imaging System ◽  
Three Dimensional ◽  
Scanning Laser ◽  
Pixel Detector ◽  
Reconstruction Algorithms ◽  
Imaging Technology ◽  
Area Array ◽  
Array Detectors ◽  
Single Pixel

Existing scanning laser three-dimensional (3D) imaging technology has slow measurement speed. In addition, the measurement accuracy of non-scanning laser 3D imaging technology based on area array detectors is limited by the resolution and response frequency of area array detectors. As a result, applications of laser 3D imaging technology are limited. This paper completed simulations and experiments of a non-scanning 3D imaging system with a single-pixel detector. The single-pixel detector can be used to achieve 3D imaging of a target by compressed sensing to overcome the shortcomings of the existing laser 3D imaging technology. First, the effects of different sampling rates, sparse transform bases, measurement matrices, and reconstruction algorithms on the measurement results were compared through simulation experiments. Second, a non-scanning 3D imaging experimental platform was designed and constructed. Finally, an experiment was performed to compare the effects of different sampling rates and reconstruction algorithms on the reconstruction effect of 3D imaging to obtain a 3D image with a resolution of 8 × 8. The simulation results show that the reconstruction effect of the Hadamard measurement matrix and the minimum total variation reconstruction algorithm performed well.

scholarly journals Principles and applications of high-speed single-pixel imaging technology

2017 ◽  
Vol 18 (9) ◽  
pp. 1261-1267 ◽  
Author(s):  
Qiang Guo ◽  
Yu-xi Wang ◽  
Hong-wei Chen ◽  
Ming-hua Chen ◽  
Si-gang Yang ◽  
...  
Keyword(s):  
High Speed ◽  
Imaging Technology ◽  
Single Pixel

Study of Single-Pixel Detection Computational Imaging Technology Based on Compressive Sensing

2013 ◽  
Vol 33 (12) ◽  
pp. 1211007 ◽  
Author(s):  
马彦鹏 Ma Yanpeng ◽  
王亚南 Wang Yanan ◽  
王义坤 Wang Yikun ◽  
葛明锋 Ge Mingfeng ◽  
王雨曦 Wang Yuxi ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Computational Imaging ◽  
Imaging Technology ◽  
Single Pixel

FROM THE BOREHOLE WALL INTO THE FORMATION – COMBINING BOREHOLE IMAGES WITH DEEP SHEAR WAVE IMAGING TECHNOLOGY

2019 ◽  
Author(s):  
Stefan Schimschal ◽  
Stephen Fayers ◽  
Nicklas Ritzmann ◽  
Martin Cox ◽  
Iain Whyte
Keyword(s):  
Shear Wave ◽  
Borehole Wall ◽  
Imaging Technology ◽  
Shear Wave Imaging ◽  
Wave Imaging

Multiresolution Bio-Medical Image Segmentation using Fuzzy C-Means Clustering

2019 ◽  
Vol 8 (4) ◽  
pp. 9548-9551
Keyword(s):  
Image Segmentation ◽  
Medical Image Segmentation ◽  
Experimental Result ◽  
Segmentation Method ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Robust Image ◽  
Multiple Clusters ◽  
Single Pixel ◽  
Popular Image

Fuzzy c-means clustering is a popular image segmentation technique, in which a single pixel belongs to multiple clusters, with varying degree of membership. The main drawback of this method is it sensitive to noise. This method can be improved by incorporating multiresolution stationary wavelet analysis. In this paper we develop a robust image segmentation method using Fuzzy c-means clustering and wavelet transform. The experimental result shows that the proposed method is more accurate than the Fuzzy c-means clustering.

Imaging Technology

2003 ◽  
Author(s):  
Detlef Winkelmann ◽  
Manfred Lutz ◽  
Damodar M. Pai ◽  
Andrew R. Melnyk ◽  
Richard Hann ◽  
...  
Keyword(s):  
Imaging Technology
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