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Title: Random On-Board Pixel Sampling (ROPS) X-Ray Camera

Abstract

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

Authors:
 [1];  [1];  [1];  [2];  [3];  [4];  [1];  [1];  [2];  [5]
  1. Los Alamos
  2. Fermilab
  3. Argonne (main)
  4. Purdue U.
  5. Nevada U., Las Vegas
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1423255
Report Number(s):
LA-UR-17-28494; FERMILAB-CONF-17-451-PPD; arXiv:1709.08659
1625782
DOE Contract Number:  
AC02-07CH11359
Resource Type:
Conference
Resource Relation:
Conference: 19th International Workshop on Radiation Imaging Detectors, Krakow, Poland, 07/02-07/06/2017
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY

Citation Formats

Wang, Zhehui, Iaroshenko, O., Li, S., Liu, T., Parab, N., Chen, W. W., Chu, P., Kenyon, G., Lipton, R., and Sun, K.-X. Random On-Board Pixel Sampling (ROPS) X-Ray Camera. United States: N. p., 2017. Web.
Wang, Zhehui, Iaroshenko, O., Li, S., Liu, T., Parab, N., Chen, W. W., Chu, P., Kenyon, G., Lipton, R., & Sun, K.-X. Random On-Board Pixel Sampling (ROPS) X-Ray Camera. United States.
Wang, Zhehui, Iaroshenko, O., Li, S., Liu, T., Parab, N., Chen, W. W., Chu, P., Kenyon, G., Lipton, R., and Sun, K.-X. Mon . "Random On-Board Pixel Sampling (ROPS) X-Ray Camera". United States. doi:. https://www.osti.gov/servlets/purl/1423255.
@article{osti_1423255,
title = {Random On-Board Pixel Sampling (ROPS) X-Ray Camera},
author = {Wang, Zhehui and Iaroshenko, O. and Li, S. and Liu, T. and Parab, N. and Chen, W. W. and Chu, P. and Kenyon, G. and Lipton, R. and Sun, K.-X.},
abstractNote = {Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Sep 25 00:00:00 EDT 2017},
month = {Mon Sep 25 00:00:00 EDT 2017}
}

Conference:
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