The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
pandangan teks lengkap
135
Teknik pemampatan tanpa kehilangan melalui penghitungan subrentetan (CSE) ialah sejenis kod enumeratif dan menggunakan model kebarangkalian yang dibina daripada rentetan bulat sumber input untuk pengekodan sumber satu dimensi (1D). CSE boleh digunakan untuk sumber dua dimensi (2D), seperti imej, dengan menangani garis piksel sumber 2D sebagai simbol abjad lanjutan. Pada langkah awal proses pengekodan CSE, kita perlu mengeluarkan bilangan kejadian semua simbol abjad lanjutan, supaya kerumitan masa meningkat secara eksponen apabila saiz sumber menjadi besar. Untuk mengurangkan masa pengiraan, kita boleh menyusun semula piksel sumber 2D menjadi rentetan sumber 1D di sepanjang lengkung mengisi ruang seperti lengkung Hilbert. Walau bagaimanapun, maklumat tentang sel bersebelahan dalam sumber 2D mungkin hilang dalam penukaran. Untuk mengurangkan kerumitan masa dan memampatkan sumber 2D tanpa menukar kepada sumber 1D, kami mencadangkan CSE baharu yang boleh mengekod sumber 2D dalam fesyen blok demi blok dan bukannya dalam fesyen baris demi baris. Algoritma yang dicadangkan menggunakan torus rata bagi sumber 2D input sebagai model kebarangkalian dan bukannya rentetan bulat sumber. Selain itu, kami membuktikan keoptimuman asimptotik algoritma yang dicadangkan untuk sumber umum 2D.
Takahiro OTA
Nagano Prefectural Institute of Technology
Hiroyoshi MORITA
The University of Electro-Communications
Akiko MANADA
Shonan Institute of Technology
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Salinan
Takahiro OTA, Hiroyoshi MORITA, Akiko MANADA, "A Universal Two-Dimensional Source Coding by Means of Subblock Enumeration" in IEICE TRANSACTIONS on Fundamentals,
vol. E102-A, no. 2, pp. 440-449, February 2019, doi: 10.1587/transfun.E102.A.440.
Abstract: The technique of lossless compression via substring enumeration (CSE) is a kind of enumerative code and uses a probabilistic model built from the circular string of an input source for encoding a one-dimensional (1D) source. CSE is applicable to two-dimensional (2D) sources, such as images, by dealing with a line of pixels of a 2D source as a symbol of an extended alphabet. At the initial step of CSE encoding process, we need to output the number of occurrences of all symbols of the extended alphabet, so that the time complexity increases exponentially when the size of source becomes large. To reduce computational time, we can rearrange pixels of a 2D source into a 1D source string along a space-filling curve like a Hilbert curve. However, information on adjacent cells in a 2D source may be lost in the conversion. To reduce the time complexity and compress a 2D source without converting to a 1D source, we propose a new CSE which can encode a 2D source in a block-by-block fashion instead of in a line-by-line fashion. The proposed algorithm uses the flat torus of an input 2D source as a probabilistic model instead of the circular string of the source. Moreover, we prove the asymptotic optimality of the proposed algorithm for 2D general sources.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.440/_p
Salinan
@ARTICLE{e102-a_2_440,
author={Takahiro OTA, Hiroyoshi MORITA, Akiko MANADA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Universal Two-Dimensional Source Coding by Means of Subblock Enumeration},
year={2019},
volume={E102-A},
number={2},
pages={440-449},
abstract={The technique of lossless compression via substring enumeration (CSE) is a kind of enumerative code and uses a probabilistic model built from the circular string of an input source for encoding a one-dimensional (1D) source. CSE is applicable to two-dimensional (2D) sources, such as images, by dealing with a line of pixels of a 2D source as a symbol of an extended alphabet. At the initial step of CSE encoding process, we need to output the number of occurrences of all symbols of the extended alphabet, so that the time complexity increases exponentially when the size of source becomes large. To reduce computational time, we can rearrange pixels of a 2D source into a 1D source string along a space-filling curve like a Hilbert curve. However, information on adjacent cells in a 2D source may be lost in the conversion. To reduce the time complexity and compress a 2D source without converting to a 1D source, we propose a new CSE which can encode a 2D source in a block-by-block fashion instead of in a line-by-line fashion. The proposed algorithm uses the flat torus of an input 2D source as a probabilistic model instead of the circular string of the source. Moreover, we prove the asymptotic optimality of the proposed algorithm for 2D general sources.},
keywords={},
doi={10.1587/transfun.E102.A.440},
ISSN={1745-1337},
month={February},}
Salinan
TY - JOUR
TI - A Universal Two-Dimensional Source Coding by Means of Subblock Enumeration
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 440
EP - 449
AU - Takahiro OTA
AU - Hiroyoshi MORITA
AU - Akiko MANADA
PY - 2019
DO - 10.1587/transfun.E102.A.440
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E102-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2019
AB - The technique of lossless compression via substring enumeration (CSE) is a kind of enumerative code and uses a probabilistic model built from the circular string of an input source for encoding a one-dimensional (1D) source. CSE is applicable to two-dimensional (2D) sources, such as images, by dealing with a line of pixels of a 2D source as a symbol of an extended alphabet. At the initial step of CSE encoding process, we need to output the number of occurrences of all symbols of the extended alphabet, so that the time complexity increases exponentially when the size of source becomes large. To reduce computational time, we can rearrange pixels of a 2D source into a 1D source string along a space-filling curve like a Hilbert curve. However, information on adjacent cells in a 2D source may be lost in the conversion. To reduce the time complexity and compress a 2D source without converting to a 1D source, we propose a new CSE which can encode a 2D source in a block-by-block fashion instead of in a line-by-line fashion. The proposed algorithm uses the flat torus of an input 2D source as a probabilistic model instead of the circular string of the source. Moreover, we prove the asymptotic optimality of the proposed algorithm for 2D general sources.
ER -