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Research on image compression encoding based on fixed dictionary.

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Název: Research on image compression encoding based on fixed dictionary.
Autoři: Li, Lifeng, Du, Yanli, Liu, Yan-Hong, Yang, Hua
Zdroj: Systems Science & Control Engineering; Dec2025, Vol. 13 Issue 1, p1-7, 7p
Témata: IMAGE compression, DATA compression, DECODING algorithms, INTERNET of things
Abstrakt: With the widespread application of IoT technology, a large amount of image data must be transmitted through networks. Owing to the current limited bandwidth, it is necessary to compress images to satisfy the requirements for real-time image transmission. Considering its innovative characteristics, a high compression ratio,and fractal compression techniques are usually adopted to code and decode images. The application of traditional fractal compression techniques is constrained by a long encoding time and low decoding accuracy, which are reduced by each image corresponding to one codebook. To address this issue, a fractal dictionary encoding (FDE) algorithm is proposed in this study. First, images with different shapes and textures were generated using a Julia fractal set(denoted as J set). Second, the generated images were segmented into a fixed-size set. A set of image blocks was obtained by expanding with a fixed-size set. Third, a fixed dictionary is created by classifying the image blocks using block truncation coding (BTC) values. Finally, the experimental results show that the FDE algorithm has a high compression ratio, high decoding accuracy and a very fast encoding and decoding speed, averaging 70 and 17 times faster than traditional fractal encoding(TFE) algorithms. The proposed algorithm satisfies the requirements for image compression. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
Popis
Abstrakt:With the widespread application of IoT technology, a large amount of image data must be transmitted through networks. Owing to the current limited bandwidth, it is necessary to compress images to satisfy the requirements for real-time image transmission. Considering its innovative characteristics, a high compression ratio,and fractal compression techniques are usually adopted to code and decode images. The application of traditional fractal compression techniques is constrained by a long encoding time and low decoding accuracy, which are reduced by each image corresponding to one codebook. To address this issue, a fractal dictionary encoding (FDE) algorithm is proposed in this study. First, images with different shapes and textures were generated using a Julia fractal set(denoted as J set). Second, the generated images were segmented into a fixed-size set. A set of image blocks was obtained by expanding with a fixed-size set. Third, a fixed dictionary is created by classifying the image blocks using block truncation coding (BTC) values. Finally, the experimental results show that the FDE algorithm has a high compression ratio, high decoding accuracy and a very fast encoding and decoding speed, averaging 70 and 17 times faster than traditional fractal encoding(TFE) algorithms. The proposed algorithm satisfies the requirements for image compression. [ABSTRACT FROM AUTHOR]
ISSN:21642583
DOI:10.1080/21642583.2024.2437160