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Повышение эффективности сжатия компьютерной графики с использованием RLE алгоритма

Повышение эффективности сжатия компьютерной графики с использованием RLE алгоритма

Abstract

На скорость работы веб-ресурса в значительной степени влияют подгружаемые внешние объекты. Наиболее часто используемые из них изображения. В связи с этим становится актуальным уменьшение размера подгружаемой компьютерной графики (изображений), чтобы уменьшить общий размер веб-страницы. Среди алгоритмов сжатия наименее востребованы алгоритмы кодирования без потерь, по причине их малой эффективности. Однако для определенного класса изображений, за счёт использования его специфических особенностей, можно получить значительно больший коэффициент сжатия при кодировании без потерь. Авторами предложена модификация RLE алгоритма, позволяющая увеличить коэффициент сжатия изображений с большими одноцветными областями.

At the speed of the web resource greatly affect loadable external objects. The most common of them the image. In this connection it becomes actual size reduction loadable computer graphics (images) to reduce the overall size of the web page. Among the least popular compression algorithms algorithms for lossless coding, because of their low efficiency. However, for a certain class of images through the use of its specific features, it is possible to obtain a much higher compression ratio in lossless coding. The authors proposed a modification of the RLE algorithm, which allows to increase the compression ratio of the images with large areas of solid color.

Keywords

RLE АЛГОРИТМ СЖАТИЯ,КОЭФФИЦИЕНТ СЖАТИЯ,ОБРАБОТКА ДАННЫХ,ОЦЕНКА ЭФФЕКТИВНОСТИ АЛГОРИТМА СЖАТИЯ,ДЛИНА ПОСЛЕДОВАТЕЛЬНОСТИ,RLE COMPRESSION ALGORITHM,THE COMPRESSION RATIO,DATA PROCESSING,EVALUATION OF THE EFFECTIVENESS OF THE COMPRESSION ALGORITHM,THE LENGTH OF THE SEQUENCE

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold