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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">scienceit</journal-id><journal-title-group><journal-title xml:lang="ru">Наука. Инновации. Технологии</journal-title><trans-title-group xml:lang="en"><trans-title>Science. Innovations. Technologies</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2308-4758</issn><publisher><publisher-name>North-Caucasus Federal University</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">scienceit-321</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>ФИЗИКО-МАТЕМАТИЧЕСКИЕ НАУКИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>PHYSICAL AND MATHEMATICAL SCIENCES</subject></subj-group></article-categories><title-group><article-title>Принцип сжатия изображений на основе дискретного вейвлет-преобразования</article-title><trans-title-group xml:lang="en"><trans-title>Principle of compression images based on discrete wavelet transform</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>Червяков</surname><given-names>Николай Иванович</given-names></name><name name-style="western" xml:lang="en"><surname>Chervyakov</surname><given-names>Nikolai Ivanovich</given-names></name></name-alternatives><email xlink:type="simple">k-fmf-primath@stavsu.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ляхов</surname><given-names>Павел Алексеевич</given-names></name><name name-style="western" xml:lang="en"><surname>Lyakhov</surname><given-names>Pavel Alexeyevich</given-names></name></name-alternatives><email xlink:type="simple">ljahov@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Калита</surname><given-names>Диана Ивановна</given-names></name><name name-style="western" xml:lang="en"><surname>Kalita</surname><given-names>Diana Ivanovna</given-names></name></name-alternatives><email xlink:type="simple">diana.kalita@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шульженко</surname><given-names>Кирилл Сергеевич</given-names></name><name name-style="western" xml:lang="en"><surname>Shulzhenko</surname><given-names>Kirill Sergeyevich</given-names></name></name-alternatives><email xlink:type="simple">kirill-joker@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Северо-Кавказский федеральный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>North Caucasus Federal University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2016</year></pub-date><pub-date pub-type="epub"><day>06</day><month>09</month><year>2022</year></pub-date><volume>0</volume><issue>3</issue><fpage>97</fpage><lpage>118</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Червяков Н.И., Ляхов П.А., Калита Д.И., Шульженко К.С., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Червяков Н.И., Ляхов П.А., Калита Д.И., Шульженко К.С.</copyright-holder><copyright-holder xml:lang="en">Chervyakov N.I., Lyakhov P.A., Kalita D.I., Shulzhenko K.S.</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://scienceit.elpub.ru/jour/article/view/321">https://scienceit.elpub.ru/jour/article/view/321</self-uri><abstract><p>В статье исследованы основные принципы сжатия изображений с применением дискретного вейвлет-преобразования. Рассмотрены перспективные методы обработки изображений EZW и SPIHT, основанные на алгоритме нульдерева. На примере показана работа метода обработки изображений SPIHT со встроенной структурой алгоритма нульдерева. Проведено моделирование в пакете прикладных программ среды MATLAB сжатия изображения в оттенках серого на основе дискретного вейвлет-преобразования. Сделан вывод о том, что пригодное для практических целей и визуально хорошего качества изображение можно получить при обнулении до 85% коэффициентов обрабатываемого изображения. При обнулении коэффициентов изображения в два раза можно получить изображение, не отличающееся по числовым характеристикам сигнал-шум и индекс структурного сходства от исходного изображения в оттенках серого.</p></abstract><trans-abstract xml:lang="en"><p>In the article the basic principles of image compression using discrete wavelet transform is presented. Promising imaging techniques EZW and SPIHT, based on zero-tree algorithm are shown. An example shows the operation of SPIHT image processing method with an integrated zero-tree algorithm structure. The simulation package application environment MATLAB compress grayscale images based on discrete wavelet transform. The conclusion is that suitable for practical purposes and visually high quality image can be obtained by resetting up to 85% of the processed image coefficients. Resetting up to 50% of the processed image coefficients allows to obtain the picture, do not differ in the numerical characteristics of the peak signal to noise ratio and the structural similarity index of the original grayscale image.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>дискретное вейвлет-преобразование</kwd><kwd>алгоритм нульдерева</kwd><kwd>метод EZW</kwd><kwd>метод SPIHT</kwd><kwd>сжатие изображения</kwd><kwd>discrete wavelet transform</kwd><kwd>zero-tree algorithm</kwd><kwd>EZW method</kwd><kwd>SPIHT method</kwd><kwd>image compression</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">D. Taubman and M. Marceilin, JPEG2000: Image Compression Fundamentals, Standards, and Practice, Kluwer, 2001.</mixed-citation><mixed-citation xml:lang="en">D. Taubman and M. 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