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Compression of signs of DCT coefficients for additional lossless compression of JPEG images

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Standard

Compression of signs of DCT coefficients for additional lossless compression of JPEG images. / Miroshnichenko, Oleksandr; Ponomarenko, Mykola; Lukin, Vladimir; Egiazarian, Karen.

Electronic Imaging: Image Processing: Algorithms and Systems XVI. Society for Imaging Science and Technology, 2018.

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Harvard

Miroshnichenko, O, Ponomarenko, M, Lukin, V & Egiazarian, K 2018, Compression of signs of DCT coefficients for additional lossless compression of JPEG images. julkaisussa Electronic Imaging: Image Processing: Algorithms and Systems XVI. Society for Imaging Science and Technology, 28/01/18. https://doi.org/10.2352/ISSN.2470-1173.2018.13.IPAS-385

APA

Miroshnichenko, O., Ponomarenko, M., Lukin, V., & Egiazarian, K. (2018). Compression of signs of DCT coefficients for additional lossless compression of JPEG images. teoksessa Electronic Imaging: Image Processing: Algorithms and Systems XVI Society for Imaging Science and Technology. https://doi.org/10.2352/ISSN.2470-1173.2018.13.IPAS-385

Vancouver

Miroshnichenko O, Ponomarenko M, Lukin V, Egiazarian K. Compression of signs of DCT coefficients for additional lossless compression of JPEG images. julkaisussa Electronic Imaging: Image Processing: Algorithms and Systems XVI. Society for Imaging Science and Technology. 2018 https://doi.org/10.2352/ISSN.2470-1173.2018.13.IPAS-385

Author

Miroshnichenko, Oleksandr ; Ponomarenko, Mykola ; Lukin, Vladimir ; Egiazarian, Karen. / Compression of signs of DCT coefficients for additional lossless compression of JPEG images. Electronic Imaging: Image Processing: Algorithms and Systems XVI. Society for Imaging Science and Technology, 2018.

Bibtex - Lataa

@inproceedings{880fe0fdb4e14ccaae563a4986a526fb,
title = "Compression of signs of DCT coefficients for additional lossless compression of JPEG images",
abstract = "One of the main approaches to additional lossless compression of JPEG images is decoding of quantized values of discrete cosine transform (DCT) coefficients and further more effective recompression of the coefficients. Values of amplitudes of DCT coefficients are highly correlated and it is possible to effectively compress them. At the same time, signs of DCT coefficients, which occupy up to 20{\%} of compressed image, are often considered unpredictable. In the paper, a new and effective method for compression of signs of quantized DCT coefficients is proposed. The proposed method takes into account both correlation between DCT coefficients of the same block and correlation between DCT coefficients of neighbor blocks. For each of 64 DCT coefficients, positions of 3 reference coefficients inside the block are determined and stored in the compressed file. Four reference coefficients with fixed positions are used from the neighbor blocks. For all reference coefficients, 15 frequency models to predict signs of a given coefficient are used. All 7 probabilities (that the sign is negative) are mixed by logistic mixing. For test set of JPEG images, we show that the proposed method allows compressing signs of DCT coefficients by 1.1 ⋯ 1.3 times, significantly outperforming nearest analogues.",
keywords = "Discrete cosine transform, JPEG, JPEG additional compression, Sign compression",
author = "Oleksandr Miroshnichenko and Mykola Ponomarenko and Vladimir Lukin and Karen Egiazarian",
note = "jufoid=84313 EXT={"}Lukin, Vladimir{"}",
year = "2018",
doi = "10.2352/ISSN.2470-1173.2018.13.IPAS-385",
language = "English",
publisher = "Society for Imaging Science and Technology",
booktitle = "Electronic Imaging",
address = "United States",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Compression of signs of DCT coefficients for additional lossless compression of JPEG images

AU - Miroshnichenko, Oleksandr

AU - Ponomarenko, Mykola

AU - Lukin, Vladimir

AU - Egiazarian, Karen

N1 - jufoid=84313 EXT="Lukin, Vladimir"

PY - 2018

Y1 - 2018

N2 - One of the main approaches to additional lossless compression of JPEG images is decoding of quantized values of discrete cosine transform (DCT) coefficients and further more effective recompression of the coefficients. Values of amplitudes of DCT coefficients are highly correlated and it is possible to effectively compress them. At the same time, signs of DCT coefficients, which occupy up to 20% of compressed image, are often considered unpredictable. In the paper, a new and effective method for compression of signs of quantized DCT coefficients is proposed. The proposed method takes into account both correlation between DCT coefficients of the same block and correlation between DCT coefficients of neighbor blocks. For each of 64 DCT coefficients, positions of 3 reference coefficients inside the block are determined and stored in the compressed file. Four reference coefficients with fixed positions are used from the neighbor blocks. For all reference coefficients, 15 frequency models to predict signs of a given coefficient are used. All 7 probabilities (that the sign is negative) are mixed by logistic mixing. For test set of JPEG images, we show that the proposed method allows compressing signs of DCT coefficients by 1.1 ⋯ 1.3 times, significantly outperforming nearest analogues.

AB - One of the main approaches to additional lossless compression of JPEG images is decoding of quantized values of discrete cosine transform (DCT) coefficients and further more effective recompression of the coefficients. Values of amplitudes of DCT coefficients are highly correlated and it is possible to effectively compress them. At the same time, signs of DCT coefficients, which occupy up to 20% of compressed image, are often considered unpredictable. In the paper, a new and effective method for compression of signs of quantized DCT coefficients is proposed. The proposed method takes into account both correlation between DCT coefficients of the same block and correlation between DCT coefficients of neighbor blocks. For each of 64 DCT coefficients, positions of 3 reference coefficients inside the block are determined and stored in the compressed file. Four reference coefficients with fixed positions are used from the neighbor blocks. For all reference coefficients, 15 frequency models to predict signs of a given coefficient are used. All 7 probabilities (that the sign is negative) are mixed by logistic mixing. For test set of JPEG images, we show that the proposed method allows compressing signs of DCT coefficients by 1.1 ⋯ 1.3 times, significantly outperforming nearest analogues.

KW - Discrete cosine transform

KW - JPEG

KW - JPEG additional compression

KW - Sign compression

U2 - 10.2352/ISSN.2470-1173.2018.13.IPAS-385

DO - 10.2352/ISSN.2470-1173.2018.13.IPAS-385

M3 - Conference contribution

BT - Electronic Imaging

PB - Society for Imaging Science and Technology

ER -