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<article article-type="research-article" dtd-version="1.3" 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" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">inform</journal-id><journal-title-group><journal-title xml:lang="ru">Информатика</journal-title><trans-title-group xml:lang="en"><trans-title>Informatics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1816-0301</issn><issn pub-type="epub">2617-6963</issn><publisher><publisher-name>UIIP NASB</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">inform-623</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОБРАБОТКА СИГНАЛОВ, ИЗОБРАЖЕНИЙ, РЕЧИ, ТЕКСТА И РАСПОЗНАВАНИЕ ОБРАЗОВ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>SIGNAL, IMAGE, SPEECH, TEXT PROCESSING AND PATTERN RECOGNITION</subject></subj-group></article-categories><title-group><article-title>УВЕЛИЧЕНИЕ РАЗРЕШЕНИЯ МУЛЬТИСПЕКТРАЛЬНЫХ ИЗОБРАЖЕНИЙ В ЦЕЛЯХ ДЕШИФРИРОВАНИЯ</article-title><trans-title-group xml:lang="en"><trans-title></trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Макаров</surname><given-names>А. О.</given-names></name></name-alternatives><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Старовойтов</surname><given-names>В. В.</given-names></name></name-alternatives><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Объединенный институт проблем информатики НАН Беларуси</institution><country>Belarus</country></aff><pub-date pub-type="collection"><year>2007</year></pub-date><pub-date pub-type="epub"><day>15</day><month>11</month><year>2018</year></pub-date><volume>0</volume><issue>2(14)</issue><fpage>16</fpage><lpage>24</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Макаров А.О., Старовойтов В.В., 2018</copyright-statement><copyright-year>2018</copyright-year><copyright-holder xml:lang="ru">Макаров А.О., Старовойтов В.В.</copyright-holder><copyright-holder xml:lang="en">Макаров А.О., Старовойтов В.В.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://inf.grid.by/jour/article/view/623">https://inf.grid.by/jour/article/view/623</self-uri><abstract><p>Предлагается новая методика увеличения разрешения мультиспектральных изображений, которая позволяет восстанавливать мультиспектральные изображения с разрешением выше, чем у панхроматического. Методика состоит из двух основных этапов: восстановления панхроматического изображения алгоритмом сверхразрешения и увеличения разрешения мультиспектрального изображения. Сверхразрешающее восстановление основано на использовании нескольких спектральных изображений для восстановления панхроматического изображения с более высоким разрешением. Алгоритм восстановления является квазиоптимальным по минимуму среднеквадратичной ошибки восстановления изображения.</p></abstract></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Kimmel, R. Demosaicing: Image reconstruction from color CCD samples / R. Kimmel // IEEE Trans. Image Processing. – 1999. – Vol. 8. – P. 1221–1228.</mixed-citation><mixed-citation xml:lang="en">Kimmel, R. Demosaicing: Image reconstruction from color CCD samples / R. Kimmel // IEEE Trans. Image Processing. – 1999. – Vol. 8. – P. 1221–1228.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Molina, R. Super resolution reconstruction of multispectral images / R. Molina, J. Mateos, A. Katsaggelos. – Sofia: Heron Press, 2005.</mixed-citation><mixed-citation xml:lang="en">Molina, R. Super resolution reconstruction of multispectral images / R. Molina, J. Mateos, A. Katsaggelos. – Sofia: Heron Press, 2005.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Zomet, A. Efficient super-resolution and applications to mosaics / A. Zomet, S. Peleg // Proc. of International Conference on Pattern Recognition. – 2000. – Vol. 1. – P. 579–583.</mixed-citation><mixed-citation xml:lang="en">Zomet, A. Efficient super-resolution and applications to mosaics / A. Zomet, S. Peleg // Proc. of International Conference on Pattern Recognition. – 2000. – Vol. 1. – P. 579–583.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">A new look at IHS-like image fusion methods / T. Tu [et al.] // Information Fusion. – 2001. – Vol. 2, № 3. – P. 177–186.</mixed-citation><mixed-citation xml:lang="en">A new look at IHS-like image fusion methods / T. Tu [et al.] // Information Fusion. – 2001. – Vol. 2, № 3. – P. 177–186.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Старовойтов, В.В. Алгоритмы регрессионного типа для увеличения разрешения мультиспектральных изображений / В.В. Старовойтов, А.О. Макаров // Информатика. – 2006. – № 3. – С. 15–26.</mixed-citation><mixed-citation xml:lang="en">Старовойтов, В.В. Алгоритмы регрессионного типа для увеличения разрешения мультиспектральных изображений / В.В. Старовойтов, А.О. Макаров // Информатика. – 2006. – № 3. – С. 15–26.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">A comparative analysis of image fusion methods / Wang Z. [et al.] // IEEE Trans. on Geoscience and Remote Sensing. – 2005. – Vol. 43, № 6. – P. 1391–1402.</mixed-citation><mixed-citation xml:lang="en">A comparative analysis of image fusion methods / Wang Z. [et al.] // IEEE Trans. on Geoscience and Remote Sensing. – 2005. – Vol. 43, № 6. – P. 1391–1402.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Довнар, Д.В. Использование ортогонализации изображений базисных функций для регуляризированного восстановления сигнала / Д.В. Довнар, К.Г. Предко // Журн. выч. ма-тем. и математич. физики. – 1986. – Т. 26. – № 7. – С. 981–993.</mixed-citation><mixed-citation xml:lang="en">Довнар, Д.В. Использование ортогонализации изображений базисных функций для регуляризированного восстановления сигнала / Д.В. Довнар, К.Г. Предко // Журн. выч. ма-тем. и математич. физики. – 1986. – Т. 26. – № 7. – С. 981–993.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Kavaldiev, D. Influence of nonuniform charge-coupled device pixel response on aperture photometry / D. Kavaldiev, Z. Ninkov // Optical Engineering. – 2001. – Vol. 40, № 2. – P. 162–169.</mixed-citation><mixed-citation xml:lang="en">Kavaldiev, D. Influence of nonuniform charge-coupled device pixel response on aperture photometry / D. Kavaldiev, Z. Ninkov // Optical Engineering. – 2001. – Vol. 40, № 2. – P. 162–169.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Dovnar, D. The orthogonalization method for error compensation of Wiener filter for spatial discreditized images / D. Dovnar, I. Zakharov // Proc. of the Eighth International Conference on Pattern Recognition and Information Processing. – Minsk, 2005. – P. 173–176.</mixed-citation><mixed-citation xml:lang="en">Dovnar, D. The orthogonalization method for error compensation of Wiener filter for spatial discreditized images / D. Dovnar, I. Zakharov // Proc. of the Eighth International Conference on Pattern Recognition and Information Processing. – Minsk, 2005. – P. 173–176.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Dovnar, D. New concept of image restoring / D. Dovnar, Y. Lebedinsky, I. Zakharov // Proc. IEEE Benelux Signal Processing. – Belgium, 2002. – P. 89–92.</mixed-citation><mixed-citation xml:lang="en">Dovnar, D. New concept of image restoring / D. Dovnar, Y. Lebedinsky, I. Zakharov // Proc. IEEE Benelux Signal Processing. – Belgium, 2002. – P. 89–92.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Zakharov, I. Super-resolution image restoration from several blurred images formed in various conditions / I. Zakharov, D. Dovnar, Y. Lebedinsky // Proc. of IEEE International Conference on Image Processing. – Barcelona, Spain, 2003. – Vol. 2. – P. 315–318.</mixed-citation><mixed-citation xml:lang="en">Zakharov, I. Super-resolution image restoration from several blurred images formed in various conditions / I. Zakharov, D. Dovnar, Y. Lebedinsky // Proc. of IEEE International Conference on Image Processing. – Barcelona, Spain, 2003. – Vol. 2. – P. 315–318.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Reeves, S.J. Blur identification by the method of generalized cross-validation / S.J. Reeves, R.M. Mersereau // IEEE Transactions on Image Processing. – 1992. – Vol. 1, № 6. – P. 119–123.</mixed-citation><mixed-citation xml:lang="en">Reeves, S.J. Blur identification by the method of generalized cross-validation / S.J. Reeves, R.M. Mersereau // IEEE Transactions on Image Processing. – 1992. – Vol. 1, № 6. – P. 119–123.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Захаров, И.Л. Алгоритмы восстановления изображений, зарегистрированных матричными фотоприемниками / И.Л. Захаров // Информатика. – 2006. – № 2 (10). – С. 64–72.</mixed-citation><mixed-citation xml:lang="en">Захаров, И.Л. Алгоритмы восстановления изображений, зарегистрированных матричными фотоприемниками / И.Л. Захаров // Информатика. – 2006. – № 2 (10). – С. 64–72.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang, Y. Problems in the fusion of commercial high resolution satellite images as well as Landsat 7 images and initial solutions / Y. Zhang // International Archives of Photogrammetry and Remote Sensing. – 2002. – Vol. 34. – Part 4.</mixed-citation><mixed-citation xml:lang="en">Zhang, Y. Problems in the fusion of commercial high resolution satellite images as well as Landsat 7 images and initial solutions / Y. Zhang // International Archives of Photogrammetry and Remote Sensing. – 2002. – Vol. 34. – Part 4.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">A comparative analysis of image fusion methods / Wang Z. [et al.] // IEEE Trans. on Geoscience and Remote Sensing. – 2005. – Vol. 43, № 6. – P. 1391–1402.</mixed-citation><mixed-citation xml:lang="en">A comparative analysis of image fusion methods / Wang Z. [et al.] // IEEE Trans. on Geoscience and Remote Sensing. – 2005. – Vol. 43, № 6. – P. 1391–1402.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Adjustable intensity-hue-saturation and Brovey transform fusion technique for IKO-NOS/Quickbird imagery / T. Tu [et al.] // Optical Engineering. – 2005. – Vol. 44, № 11. – P. 116201-1–116201-10.</mixed-citation><mixed-citation xml:lang="en">Adjustable intensity-hue-saturation and Brovey transform fusion technique for IKO-NOS/Quickbird imagery / T. Tu [et al.] // Optical Engineering. – 2005. – Vol. 44, № 11. – P. 116201-1–116201-10.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Wald, L. Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images / L. Wald, T. Ranchin, M. Mangolini // Photogrammetric Engineering &amp; Remote Sensing. – 1997. – Vol. 63, № 6. – P. 691–699.</mixed-citation><mixed-citation xml:lang="en">Wald, L. Fusion of satellite images of different spatial resolutions: Assessing the quality of resulting images / L. Wald, T. Ranchin, M. Mangolini // Photogrammetric Engineering &amp; Remote Sensing. – 1997. – Vol. 63, № 6. – P. 691–699.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
