Ternary Data Categorization for Evaluating the Impact of Data Transforms on Image Compressibility

Ternary Data Categorization for Evaluating the Impact of Data Transforms on Image Compressibility

Článek WoS

In our increasingly digital world, data compression remains an important research topic. One way to improve the compression ratio is to use data transform techniques to increase further compressibility of input data for specific compression algorithms. This paper introduces a novel ternary data categorization in order to evaluate the impact of data transform techniques on input data. The categorization is described and explained in detail. Then, three transforms used for testing are described: BurrowsWheeler and Move-to-Front transforms (BWT and MTF), as well as shifting summation. These transforms are applied to the eight true color images from the Kodak and Kaggle image sets. The findings derived from the ternary graphs and statistical measures indicate that combining BWT and MTF transforms yields the best results for this test on the selected image data. The shifting summation approach opens up possibilities for further research, particularly in searching for data patterns.

In our increasingly digital world, data compression remains an important research topic. One way to improve the compression ratio is to use data transform techniques to increase further compressibility of input data for specific compression algorithms. This paper introduces a novel ternary data categorization in order to evaluate the impact of data transform techniques on input data. The categorization is described and explained in detail. Then, three transforms used for testing are described: BurrowsWheeler and Move-to-Front transforms (BWT and MTF), as well as shifting summation. These transforms are applied to the eight true color images from the Kodak and Kaggle image sets. The findings derived from the ternary graphs and statistical measures indicate that combining BWT and MTF transforms yields the best results for this test on the selected image data. The shifting summation approach opens up possibilities for further research, particularly in searching for data patterns.

Ternary categorization, ternary diagram, image compression, data transform, transform evaluation

Ternary categorization, ternary diagram, image compression, data transform, transform evaluation

SAMOFALOV, A.; POLÁK, L.

2026

01.04.2026

Spolecnost Pro Radioelektronicke Inzenyrstvi

Radioengineering

35

1

Česká republika

164

175

12

https://www.radioeng.cz/fulltexts/2026/26_01_0164_0175.pdf