Strange Images in Remote Sensing and Their Properties
Lossy image compression is used in many applications including remote sensing. Image size and number increase and this often leads to the necessity to apply image compression. In lossy compression, it is assumed that rate-distortion curves are monotonous functions and this assumption is put into bas...
Збережено в:
| Дата: | 2023 |
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| Автори: | , , , , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine
2023
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| Теми: | |
| Онлайн доступ: | https://ujrs.org.ua/ujrs/article/view/240 |
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| Назва журналу: | Ukrainian Journal of Remote Sensing of the Earth |
Репозитарії
Ukrainian Journal of Remote Sensing of the Earth| Резюме: | Lossy image compression is used in many applications including remote sensing. Image size and number increase and this often leads to the necessity to apply image compression. In lossy compression, it is assumed that rate-distortion curves are monotonous functions and this assumption is put into basis of compression control. However, it has been shown recently that there are grayscale and color images called “strange” for which the rate-distortion curves are not monotonous. In this paper, we demonstrate that some remote sensing images can be strange as well and this takes place for JPEG and some other compression techniques. Analysis of properties for strange images using Spearman rank order correlation coefficient is carried out and it is shown that there several parameters characterizing image complexity that have a rather high correlation with probability that a given image is strange. For example, image entropy is one of such parameters. |
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