<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462013000400009</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[On Efficiency of Detection of Subpixel Targets with Hypothesis Dependent Structured Background Power]]></article-title>
<article-title xml:lang="es"><![CDATA[Sobre la eficiencia de detección de objetos subpixeleados con potencia de fondo estructurado que depende de hipótesis]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Golikov]]></surname>
<given-names><![CDATA[Víctor]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lebedeva]]></surname>
<given-names><![CDATA[Olga]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[May Alarcón]]></surname>
<given-names><![CDATA[Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Méndez Martínez]]></surname>
<given-names><![CDATA[Francisco]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rodríguez Blanco]]></surname>
<given-names><![CDATA[Marco]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Islas Chuc]]></surname>
<given-names><![CDATA[Mayólo Salvador]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Universidad Autónoma del Carmen Facultad de Ingeniería ]]></institution>
<addr-line><![CDATA[Ciudad del Carmen Campeche]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2013</year>
</pub-date>
<volume>17</volume>
<numero>4</numero>
<fpage>561</fpage>
<lpage>568</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462013000400009&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462013000400009&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462013000400009&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[In this paper, matched detector (MD) and matched subspace detector (MSD) are studied when the structured background power is different under the null and the alternative hypotheses. The distributions of two test statistics are derived under these conditions. It has been analytically shown that these detectors can suffer a drastic degradation in performance for background power deviations under alternative hypothesis. We discuss the differences between the performances of these detectors in the case of the structured and unstructured backgrounds with uncorrelated Gaussian noise. The theoretical results are compared with simulated data and good agreement is reported. We present experimental results of small floating object detection on an agitated sea surface using spectral digital video experiments which validate the theoretical results.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[El detector acoplado (MD) y el detector de subespacio acoplado (MSD) son estudiados cuando la potencia de fondo estructurado es diferente bajo las hipótesis alternativa y nula. Las distribuciones de las dos pruebas estadísticas son realizadas bajo las mismas condiciones. Ha sido analíticamente demostrado que esos dos detectores pueden sufrir una degradación drástica de su eficiencia para las desviaciones de la potencia de fondo bajo hipótesis alternativas. Se discuten las diferencias entre los rendimientos de esos detectores en el caso de fondos estructurados y no estructurados con ruido Gaussiano no correlacionado. Los resultados teóricos son comparados con los datos simulados y una buena concordancia es reportada. Se presentan resultados experimentales de la detección de objetos pequeños flotando en la superficie agitada del mar, usando el experimento del video digital espectral, que demuestra la validación de los resultados teóricos.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Hypothesis dependent power]]></kwd>
<kwd lng="en"><![CDATA[subpixel targets]]></kwd>
<kwd lng="en"><![CDATA[performance loss]]></kwd>
<kwd lng="es"><![CDATA[Potencia que depende de hipótesis]]></kwd>
<kwd lng="es"><![CDATA[objetos subpixeleados]]></kwd>
<kwd lng="es"><![CDATA[pérdida de eficiencia]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[  	    <p align="justify"><font face="verdana" size="4">Art&iacute;culos regulares</font></p>  	    <p align="center"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="center"><font face="verdana" size="4"><b>On Efficiency of Detection of Subpixel Targets with Hypothesis Dependent Structured Background Power</b></font></p>  	    <p align="center"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="center"><font face="verdana" size="3"><b>Sobre la eficiencia de detecci&oacute;n de objetos subpixeleados con potencia de fondo estructurado que depende de hip&oacute;tesis</b></font></p>  	    <p align="center"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="center"><font face="verdana" size="2"><b>V&iacute;ctor Golikov, Olga Lebedeva, Manuel May Alarc&oacute;n, Francisco M&eacute;ndez Mart&iacute;nez, Marco Rodr&iacute;guez Blanco, and May&oacute;lo Salvador Islas Chuc</b></font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><i>Facultad de Ingenier&iacute;a, Universidad Aut&oacute;noma del Carmen, Ciudad del Carmen, Campeche, M&eacute;xico</i>. <a href="mailto:vgolikov@pampano.unacar.mx">vgolikov@pampano.unacar.mx</a>, <a href="mailto:olebedeva@pampano.unacar.mx">olebedeva@pampano.unacar.mx</a>, <a href="mailto:mmay@pampano.unacar.mx">mmay@pampano.unacar.mx</a>, <a href="mailto:fmendez@pampano.unacar.mx">fmendez@pampano.unacar.mx</a></font></p>  	    ]]></body>
<body><![CDATA[<p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2">Article received on 18/03/2012    <br> 	Accepted on 18/06/2013</font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><b>Abstract</b></font></p>  	    <p align="justify"><font face="verdana" size="2">In this paper, matched detector (MD) and matched subspace detector (MSD) are studied when the structured background power is different under the null and the alternative hypotheses. The distributions of two test statistics are derived under these conditions. It has been analytically shown that these detectors can suffer a drastic degradation in performance for background power deviations under alternative hypothesis. We discuss the differences between the performances of these detectors in the case of the structured and unstructured backgrounds with uncorrelated Gaussian noise. The theoretical results are compared with simulated data and good agreement is reported. We present experimental results of small floating object detection on an agitated sea surface using spectral digital video experiments which validate the theoretical results.</font></p>  	    <p align="justify"><font face="verdana" size="2"><b>Keywords:</b> Hypothesis dependent power, subpixel targets, performance loss.</font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><b>Resumen</b></font></p>  	    <p align="justify"><font face="verdana" size="2">El detector acoplado (MD) y el detector de subespacio acoplado (MSD) son estudiados cuando la potencia de fondo estructurado es diferente bajo las hip&oacute;tesis alternativa y nula. Las distribuciones de las dos pruebas estad&iacute;sticas son realizadas bajo las mismas condiciones. Ha sido anal&iacute;ticamente demostrado que esos dos detectores pueden sufrir una degradaci&oacute;n dr&aacute;stica de su eficiencia para las desviaciones de la potencia de fondo bajo hip&oacute;tesis alternativas. Se discuten las diferencias entre los rendimientos de esos detectores en el caso de fondos estructurados y no estructurados con ruido Gaussiano no correlacionado. Los resultados te&oacute;ricos son comparados con los datos simulados y una buena concordancia es reportada. Se presentan resultados experimentales de la detecci&oacute;n de objetos peque&ntilde;os flotando en la superficie agitada del mar, usando el experimento del video digital espectral, que demuestra la validaci&oacute;n de los resultados te&oacute;ricos.</font></p>  	    ]]></body>
<body><![CDATA[<p align="justify"><font face="verdana" size="2"><b>Palabras clave</b>. Potencia que depende de hip&oacute;tesis, objetos subpixeleados, p&eacute;rdida de eficiencia.</font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><a href="/pdf/cys/v17n4/v17n4a9.pdf" target="_blank">DESCARGAR ART&Iacute;CULO EN FORMATO PDF</a></font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><b>Acknowledgements</b></font></p>  	    <p align="justify"><font face="verdana" size="2">This work has been funded by CONACYT (project number 80994).</font></p>  	    <p align="justify"><font face="verdana" size="2">&nbsp;</font></p>  	    <p align="justify"><font face="verdana" size="2"><b>References</b></font></p>  	    <!-- ref --><p align="justify"><font face="verdana" size="2"><b>1. Manolakis, D., Siracusa, C., &amp; Shaw, G. (2001).</b> HyperspectralSubpixel Target Detection Using the Linear Mixing Model. <i>IEEE Transactions on Geoscience and Remote Sensing,</i> 39(7), 1392&#45;1409.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064058&pid=S1405-5546201300040000900001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    ]]></body>
<body><![CDATA[<!-- ref --><p align="justify"><font face="verdana" size="2"><b>2. Chang, C.&#45;I. (2005).</b> Orthogonal Subspace projection (OSP) Revisited: A Comprehensive Study and Analysis. <i>IEEE Transactions on Geoscience and Remote Sensing,</i> 43(3), 502&#45;518.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064060&pid=S1405-5546201300040000900002&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    <!-- ref --><p align="justify"><font face="verdana" size="2"><b>3. Thai, B.&amp; Healey, G. (2002).</b> Invariant Subpixel Material Detection in Hyperspectral Imagery. <i>IEEE Transactions on Geoscience and Remote Sensing,</i> 40(3), 599&#45;608.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064062&pid=S1405-5546201300040000900003&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    <!-- ref --><p align="justify"><font face="verdana" size="2"><b>4. Bajorski, P. (2007).</b> Analytical Comparison of the Matched Filter and Orthogonal Subspace Projection Detectors for Hyperspectral Images. <i>IEEE Transactions on Geoscience and Remote</i> <i>Sensing,</i> 45(7), 2394&#45;2402.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064064&pid=S1405-5546201300040000900004&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    <!-- ref --><p align="justify"><font face="verdana" size="2"><b>5. Vincent, F., Besson, O., &amp; Richard, C. (2008</b>).Matched Subspace Detection With Hypothesis Dependent Noise Power. <i>IEEE Transactions on Signal Processing,</i> 56(11), 5713&#45;5718.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064066&pid=S1405-5546201300040000900005&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    <!-- ref --><p align="justify"><font face="verdana" size="2"><b>6. Manolakis, D. &amp; Shaw, G. (2002).</b> Detection Algorithms for Hyperspectral Imaging Applications. <i>IEEE Signal Processing Magazine,</i> 19(1), 29&#45;43.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=2064068&pid=S1405-5546201300040000900006&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></font></p>  	    ]]></body>
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