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Title: Accelerated signal encoding and reconstruction using pixon method

Abstract

The method identifies a Pixon element, which is a fundamental and indivisible unit of information, and a Pixon basis, which is the set of possible functions from which the Pixon elements are selected. The actual Pixon elements selected from this basis during the reconstruction process represents the smallest number of such units required to fit the data and representing the minimum number of parameters necessary to specify the image. The Pixon kernels can have arbitrary properties (e.g., shape, size, and/or position) as needed to best fit the data.

Inventors:
; ;
Issue Date:
Research Org.:
The Regents of the University of California, Oakland, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1175360
Patent Number(s):
6,895,125
Application Number:
10/308,450
Assignee:
The Regents of the University of California (Oakland, CA) OSTI
DOE Contract Number:  
FG02-87ER40317
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Puetter, Richard, Yahil, Amos, and Pina, Robert. Accelerated signal encoding and reconstruction using pixon method. United States: N. p., 2005. Web.
Puetter, Richard, Yahil, Amos, & Pina, Robert. Accelerated signal encoding and reconstruction using pixon method. United States.
Puetter, Richard, Yahil, Amos, and Pina, Robert. Tue . "Accelerated signal encoding and reconstruction using pixon method". United States. https://www.osti.gov/servlets/purl/1175360.
@article{osti_1175360,
title = {Accelerated signal encoding and reconstruction using pixon method},
author = {Puetter, Richard and Yahil, Amos and Pina, Robert},
abstractNote = {The method identifies a Pixon element, which is a fundamental and indivisible unit of information, and a Pixon basis, which is the set of possible functions from which the Pixon elements are selected. The actual Pixon elements selected from this basis during the reconstruction process represents the smallest number of such units required to fit the data and representing the minimum number of parameters necessary to specify the image. The Pixon kernels can have arbitrary properties (e.g., shape, size, and/or position) as needed to best fit the data.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2005},
month = {5}
}

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