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Histogram computation based on image bitwise decomposition

Andres Frias Velazquez UGent and Ramon Morros (2009) 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6. p.3269-3272
abstract
In this paper, a new method to compute the image histogram is presented, along with the image maximum and minimum values. It is intended for highly parallel architectures such as the ones found in Focal Plane Processors (FPP). This new approach exploits this parallelism relying on the privatization technique to avoid the memory collision problem, while the bin frequency is obtained through image bitwise manipulation. Unlike traditional privatization techniques, our method exhibits a trade off between processing time and bin size. That is, it can be adapted as a power-of-two bin size histogram and the computation time decreases exponentially as the bin size is reduced on each power of two, allowing high computational flexibility.
Please use this url to cite or link to this publication:
author
organization
year
type
conference (proceedingsPaper)
publication status
published
subject
keyword
Bitwise decomposition, Hardware, Focal Plane Processor, Histogram
in
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6
pages
3269 - 3272
publisher
IEEE
place of publication
New York, NY, USA
conference name
16th IEEE International Conference on Image Processing (ICIP 2009)
conference location
Cairo, Egypt
conference start
2009-11-07
conference end
2009-11-10
Web of Science type
Proceedings Paper
Web of Science id
000280464301265
ISBN
9781424456536
DOI
10.1109/ICIP.2009.5413981
language
English
UGent publication?
no
classification
P1
id
1053584
handle
http://hdl.handle.net/1854/LU-1053584
date created
2010-10-05 15:10:28
date last changed
2017-01-02 09:52:19
@inproceedings{1053584,
  abstract     = {In this paper, a new method to compute the image histogram is presented, along with the image maximum and minimum values. It is intended for highly parallel architectures such as the ones found in Focal Plane Processors (FPP). This new approach exploits this parallelism relying on the privatization technique to avoid the memory collision problem, while the bin frequency is obtained through image bitwise manipulation. Unlike traditional privatization techniques, our method exhibits a trade off between processing time and bin size. That is, it can be adapted as a power-of-two bin size histogram and the computation time decreases exponentially as the bin size is reduced on each power of two, allowing high computational 
flexibility.},
  author       = {Frias Velazquez, Andres and Morros, Ramon },
  booktitle    = {2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6},
  isbn         = {9781424456536},
  keyword      = {Bitwise decomposition,Hardware,Focal Plane Processor,Histogram},
  language     = {eng},
  location     = {Cairo, Egypt},
  pages        = {3269--3272},
  publisher    = {IEEE},
  title        = {Histogram computation based on image bitwise decomposition},
  url          = {http://dx.doi.org/10.1109/ICIP.2009.5413981},
  year         = {2009},
}

Chicago
Frias Velazquez, Andres, and Ramon Morros. 2009. “Histogram Computation Based on Image Bitwise Decomposition.” In 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6, 3269–3272. New York, NY, USA: IEEE.
APA
Frias Velazquez, A., & Morros, R. (2009). Histogram computation based on image bitwise decomposition. 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6 (pp. 3269–3272). Presented at the 16th IEEE International Conference on Image Processing (ICIP 2009), New York, NY, USA: IEEE.
Vancouver
1.
Frias Velazquez A, Morros R. Histogram computation based on image bitwise decomposition. 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6. New York, NY, USA: IEEE; 2009. p. 3269–72.
MLA
Frias Velazquez, Andres, and Ramon Morros. “Histogram Computation Based on Image Bitwise Decomposition.” 2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6. New York, NY, USA: IEEE, 2009. 3269–3272. Print.