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2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security (BLISS 2007)
Image Analysis by Means of the Stochastic Matrix Method of Function Recovery
Edinburgh, United Kingdom
August 09-August 10
ISBN: 0-7695-2919-4
ASCII Text
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Daniel Howard, Joseph Kolibal, "Image Analysis by Means of the Stochastic Matrix Method of Function Recovery," Bio-inspired, Learning, and Intelligent Systems for Security, ECSIS Symposium on, pp. 97-101, 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security (BLISS 2007), 2007.
 
 
BibTex
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@article{ 10.1109/BLISS.2007.14,
author = {Daniel Howard and Joseph Kolibal},
title = {Image Analysis by Means of the Stochastic Matrix Method of Function Recovery},
journal ={Bio-inspired, Learning, and Intelligent Systems for Security, ECSIS Symposium on},
volume = {0},
year = {2007},
isbn = {0-7695-2919-4},
pages = {97-101},
doi = {http://doi.ieeecomputersociety.org/10.1109/BLISS.2007.14},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Bio-inspired, Learning, and Intelligent Systems for Security, ECSIS Symposium on
TI - Image Analysis by Means of the Stochastic Matrix Method of Function Recovery
SN - 0-7695-2919-4
SP97
EP101
A1 - Daniel Howard,
A1 - Joseph Kolibal,
PY - 2007
KW - null
VL - 0
JA - Bio-inspired, Learning, and Intelligent Systems for Security, ECSIS Symposium on
ER -
 
Daniel Howard, Senior Member IEEE
Joseph Kolibal, University of Southern Mississippi, USA
The recently patented stochastic matrix method of function recovery offers workable alternatives to traditional methods of image analysis. This paper illustrates its application to image compression and its application to image enhancement (image zoom). In the former application, it appears to be competitive with JPEG DCT with respect to file size but with the added advantage that it does not suffer from artifacts of that coder. In the latter application, it appears to be clearly superior to the bi-cubic interpolation that is used by popular commercial graphics packages. An important and characteristic property of the stochastic matrix method (SMM) of function recovery is its free parameter \sigma that can be optimized, e.g. by an intelligent system, to change the nature of the image analysis.
Citation:
Daniel Howard, Joseph Kolibal, "Image Analysis by Means of the Stochastic Matrix Method of Function Recovery," bliss, pp.97-101, 2007 ECSIS Symposium on Bio-inspired, Learning, and Intelligent Systems for Security (BLISS 2007), 2007
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