informИнформатикаInformatics1816-03012617-6963UIIP NASB10.37661/1816-0301-2022-19-2-7-25inform-1197Research ArticleОБРАБОТКА СИГНАЛОВ, ИЗОБРАЖЕНИЙ, РЕЧИ, ТЕКСТА И РАСПОЗНАВАНИЕ ОБРАЗОВSIGNAL, IMAGE, SPEECH, TEXT PROCESSING AND PATTERN RECOGNITIONУменьшение динамического диапазона инфракрасных изображений на основе блочно-приоритетного выравнивания и сжатия гистограммReducing the dynamic range of infrared images based on block-priority equalization and compression of histogramshttps://orcid.org/0000-0002-9612-9487РудиковС. И.RudikovS. I.

Рудиков Станислав Игоревич, магистр технических наук, заместитель директора по информационным техно-логиям

ул. Макаенка, 23, корп.1, Минск, 220114, Беларусь

Stanislav I. Rudikov, M. Sc. (Eng.), Information Technology Deputy Director

st. Makayonok 23/1, Minsk, 220114, Belarus

stanislav.rudikov@gmail.comЦветковВ. Ю.TsviatkouV. Yu.

Цветков Виктор Юрьевич, доктор технических наук, профессор, заведующий кафедрой инфокоммуникационных технологий

ул. П. Бровки, 6, Минск, 220013, Беларусь

Viktar Yu. Tsviatkou, D. Sc. (Eng.), Prof., Head of the Department of Infocommunication Technologies

st. P. Brovki, 6, Minsk, 220013, Belarus

vtsvet@bsuir.byШкадаревичА. П.ShkadarevichA. P.

Шкадаревич Алексей Петрович, академик Националь-ной академии наук Беларуси, доктор физико-математических наук, профессор, директор

ул. Макаенка, 23, корп.1, Минск, 220114, Беларусь

Alexey P. Shkadarevich, Academician of the National Academy of Science of Belarus, D. Sc. (Phys.-Math.), Prof., Director

st. Makayonok 23/1, Minsk, 220114, Belarus

office@lemt.byНаучно-технический центр «ЛЭМТ» БелОМОScientific and Technical Center LEMT of the BelOMOБелорусский государственный университет информатики и радиоэлектроникиBelarusian State University of Informatics and Radioelectronics202211042022192725Copyright © Рудиков С.И., Цветков В.Ю., Шкадаревич А.П., 20222022Рудиков С.И., Цветков В.Ю., Шкадаревич А.П.Rudikov S.I., Tsviatkou V.Y., Shkadarevich A.P.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://inf.grid.by/jour/article/view/1197Цели

Цели. Рассматривается задача уменьшения динамического диапазона инфракрасных изображений для их воспроизведения на устройствах отображения с узким динамическим диапазоном. Исследуется метод адаптивного выравнивания гистограммы изображения на основе интегральной функции распределения яркости. Для преобразования яркости пиксела этот метод использует аппроксимацию локальных значений выравнивания ближайших блоков пикселов, на которые делится исходное изображение. Это повышает локальный контраст изображения, но приводит к высокой вычислительной сложности, которая растет с уменьшением размера блока. Целью работы является снижение вычислительной сложности адаптивного выравнивания и сжатия гистограмм инфракрасных изображений при уменьшении их динамического диапазона.

Методы

Методы. Используются методы обработки изображений.

Результаты

Результаты. Для уменьшения вычислительной сложности преобразования динамического диапазона инфракрасных изображений предложена блочно-приоритетная модификация метода адаптивного выравнивания гистограммы. Модификация основана на разделении множества блоков изображения на подмножества высокоприоритетных и низкоприоритетных блоков в зависимости от их яркостных статистических свойств. При интерполяции значений пикселов для высокоприоритетных блоков используются локальные значения выравнивания, а для низкоприоритетных блоков – общие значения выравнивания.

В результате общее число векторов выравнивания сокращается пропорционально соотношению размеров подмножеств и снижается вычислительная сложность преобразования динамического диапазона.

Заключение

Заключение. При изменении отношения количества высокоприоритетных блоков пикселов инфракрасного изображения к количеству всех блоков в диапазоне 0,25–0,75 предложенный алгоритм более эффективен по сравнению с алгоритмами глобального и адаптивного выравнивания гистограммы.

Objectives

Objectives. The problem of reducing the dynamic range of infrared images for their reproduction on display devices with a narrow dynamic range is considered. The method of local image histogram equalization based on the integral distribution function of brightness is investigated. To transform the brightness of a pixel, this method uses an approximation of the local alignment values of the nearest blocks of pixels of original image. This in-creases the local contrast of the image, but leads to high computational complexity, which is increasing while block size decreases. The aim of the work is to reduce the computational complexity of adaptive equalization and compression of infrared image histograms while reducing their dynamic range.

Methods

Methods. Image processing methods are used.

Results

Results. To reduce the computational complexity of transforming the dynamic range of infrared images, a block-priority modification of the adaptive histogram equalization method is proposed. The modification is based on the division of the set of image blocks into two subsets of high-priority and low-priority blocks depend-ing on their brightness statistical properties. When interpolating pixel values, high-priority blocks use local alignment values, and low-priority blocks use global alignment values. As a result, the total number of alignment vectors is reduced in proportion to the ratio of subsets sizes and the computational complexity of the dynamic range transformation is reduced.

Conclusion

Conclusion. When changing the ratio of the number of high-priority blocks of infrared image pixels to the number of all blocks in the range of 0.25–0.75, the proposed algorithm is more efficient than global and adaptive histogram equalization algorithms.

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The authors declare that there are no conflicts of interest present.