Hierarchical bilevel image compression based on cutset sampling

Shengxin Zha; Thrasyvoulos N Pappas; David L. Neuhoff

doi:10.1109/ICIP.2012.6467410

Hierarchical bilevel image compression based on cutset sampling

Shengxin Zha^*, Thrasyvoulos N Pappas, David L. Neuhoff

^*Corresponding author for this work

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Scopus citations

Abstract

We propose a hierarchical lossy bilevel image compression method that relies on adaptive cutset sampling (along lines of a rectangular grid with variable block size) and Markov Random Field based reconstruction. It is an efficient encoding scheme that preserves image structure by using a coarser grid in smooth areas of the image and a finer grid in areas with more detail. Experimental results demonstrate that the proposed method performs as well as or better than the fixed-grid approach, and outperforms other lossy bilevel compression methods in its rate-distortion performance.

Original language	English (US)
Title of host publication	2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages	2517-2520
Number of pages	4
DOIs	https://doi.org/10.1109/ICIP.2012.6467410
State	Published - Dec 1 2012
Event	2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States Duration: Sep 30 2012 → Oct 3 2012

Other

Other	2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/Territory	United States
City	Lake Buena Vista, FL
Period	9/30/12 → 10/3/12

Keywords

arithmetic coding
MRF
rate-distortion
structurally lossless compression

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems

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10.1109/ICIP.2012.6467410

Cite this

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title = "Hierarchical bilevel image compression based on cutset sampling",

abstract = "We propose a hierarchical lossy bilevel image compression method that relies on adaptive cutset sampling (along lines of a rectangular grid with variable block size) and Markov Random Field based reconstruction. It is an efficient encoding scheme that preserves image structure by using a coarser grid in smooth areas of the image and a finer grid in areas with more detail. Experimental results demonstrate that the proposed method performs as well as or better than the fixed-grid approach, and outperforms other lossy bilevel compression methods in its rate-distortion performance.",

keywords = "arithmetic coding, MRF, rate-distortion, structurally lossless compression",

author = "Shengxin Zha and Pappas, {Thrasyvoulos N} and Neuhoff, {David L.}",

year = "2012",

month = dec,

day = "1",

doi = "10.1109/ICIP.2012.6467410",

language = "English (US)",

isbn = "9781467325332",

pages = "2517--2520",

booktitle = "2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings",

note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",

}

Zha, S, Pappas, TN & Neuhoff, DL 2012, Hierarchical bilevel image compression based on cutset sampling. in 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings., 6467410, pp. 2517-2520, 2012 19th IEEE International Conference on Image Processing, ICIP 2012, Lake Buena Vista, FL, United States, 9/30/12. https://doi.org/10.1109/ICIP.2012.6467410

TY - GEN

T1 - Hierarchical bilevel image compression based on cutset sampling

AU - Zha, Shengxin

AU - Pappas, Thrasyvoulos N

AU - Neuhoff, David L.

PY - 2012/12/1

Y1 - 2012/12/1

N2 - We propose a hierarchical lossy bilevel image compression method that relies on adaptive cutset sampling (along lines of a rectangular grid with variable block size) and Markov Random Field based reconstruction. It is an efficient encoding scheme that preserves image structure by using a coarser grid in smooth areas of the image and a finer grid in areas with more detail. Experimental results demonstrate that the proposed method performs as well as or better than the fixed-grid approach, and outperforms other lossy bilevel compression methods in its rate-distortion performance.

AB - We propose a hierarchical lossy bilevel image compression method that relies on adaptive cutset sampling (along lines of a rectangular grid with variable block size) and Markov Random Field based reconstruction. It is an efficient encoding scheme that preserves image structure by using a coarser grid in smooth areas of the image and a finer grid in areas with more detail. Experimental results demonstrate that the proposed method performs as well as or better than the fixed-grid approach, and outperforms other lossy bilevel compression methods in its rate-distortion performance.

KW - arithmetic coding

KW - MRF

KW - rate-distortion

KW - structurally lossless compression

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U2 - 10.1109/ICIP.2012.6467410

DO - 10.1109/ICIP.2012.6467410

M3 - Conference contribution

AN - SCOPUS:84875827751

SN - 9781467325332

SP - 2517

EP - 2520

BT - 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings

T2 - 2012 19th IEEE International Conference on Image Processing, ICIP 2012

Y2 - 30 September 2012 through 3 October 2012

ER -

Hierarchical bilevel image compression based on cutset sampling

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Keywords

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