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                    <article article-type="research-article">
                    <front>
                        <journal-meta>
                        <journal-id journal-id-type="publisher-id">ei</journal-id>
                        <journal-title>Electronic Imaging</journal-title>
                        <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub">2470-1173</issn>
                        <publisher>
                            <publisher-name>Society for Imaging Science and Technology</publisher-name>
                            <publisher-loc>IS&amp;T 7003 Kilworth Lane, Springfield, VA 22151 USA</publisher-loc>
                        </publisher>
                        </journal-meta>
                        <article-meta>
                        <article-id pub-id-type="doi">10.2352/EI.2022.34.10.IPAS-354</article-id>
                        <article-id pub-id-type="publisher-id">IPAS-354</article-id>
                        <article-categories>
                            <subj-group>
                            <subject>Article</subject>
                            </subj-group>
                        </article-categories>
                        <title-group>
                            <article-title>On properties of visual quality metrics in remote sensing applications</article-title>
                        </title-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Ieremeiev</surname>
                                <given-names>Oleg </given-names>
                               </name> <xref ref-type="aff" rid="aff1author1"/></contrib><aff id="aff1author1">National Aerospace University, Ukraine</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Lukin</surname>
                                <given-names>Vladimir </given-names>
                               </name> <xref ref-type="aff" rid="aff1author2"/></contrib><aff id="aff1author2">National Aerospace University, Ukraine</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Okarma</surname>
                                <given-names>Krzysztof </given-names>
                               </name> <xref ref-type="aff" rid="aff2author3"/></contrib><aff id="aff2author3">West Pomeranian University of Technology, Poland</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Egiazarian</surname>
                                <given-names>Karen </given-names>
                               </name> <xref ref-type="aff" rid="aff3author4"/></contrib><aff id="aff3author4">Tampere University of Technology, Finland</aff></contrib-group><contrib-group content-type="all"><contrib contrib-type="author"><name>
                                <surname>Vozel</surname>
                                <given-names>Benoit </given-names>
                               </name> <xref ref-type="aff" rid="aff4author5"/></contrib><aff id="aff4author5">University of Rennes 1, France</aff></contrib-group><abstract>
                        <title>Abstract</title>
                        <p>Visual quality is important for remote sensing data presented as grayscale, color or pseudo-color images. Although several visual quality metrics (VQMs) have been used to characterize such data, only a limited analysis of their applicability in remote sensing applications has been done so far. In this paper, we study correlation factors for a wide set of VQMs for color images with distortion types typical for remote sensing. It is demonstrated that there are many metrics that have very high Spearman rank order correlation, e.g. PSNR-based and SSIM-based metrics. Meanwhile, there are also metrics that are practically uncorrelated with others. A detailed analysis of VQMs that have the largest SROCC values and belong to different groups is presented in this paper.</p>
                        </abstract><pub-date>
                            <day>16</day>
                            <month>01</month>
                            <year>2022</year>
                            </pub-date><volume>34</volume>
                        <issue-acronym>IPAS</issue-acronym>
                        <issue>10</issue>
                        <fpage>354-1</fpage>
                        <lpage>354-6</lpage>
                        <permissions>
                             <copyright-statement>© 2022, Society for Imaging Science and Technology</copyright-statement>
                            <copyright-year>2022</copyright-year>
                        </permissions><kwd-group><kwd>visual quality</kwd><kwd> remote sensing image</kwd><kwd> correlation analysis</kwd><kwd> neural network</kwd></kwd-group></article-meta>
                    </front>
                    </article>