Near-lossless Image Compression with Parity Reduction

Basar Koc; Ziya Arnavut; Sergey Voronin; Huseyin Kocak

doi:10.1109/INES49302.2020.9147124

Near-lossless Image Compression with Parity Reduction

Basar Koc, Ziya Arnavut, Sergey Voronin, Huseyin Kocak

Computer Science

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

Abstract

In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.

Original language	English (US)
Title of host publication	INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	225-229
Number of pages	5
ISBN (Electronic)	9781728110592
DOIs	https://doi.org/10.1109/INES49302.2020.9147124
State	Published - Jul 2020
Event	24th IEEE International Conference on Intelligent Engineering Systems, INES 2020 - Reykjavik, Iceland Duration: Jul 8 2020 → Jul 10 2020

Publication series

Name	INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings

Conference

Conference	24th IEEE International Conference on Intelligent Engineering Systems, INES 2020
Country	Iceland
City	Reykjavik
Period	7/8/20 → 7/10/20

Keywords

BWIC_I
JPEG
JPEG 2000
Least significant bit
Near-lossless image compression
Parity reduction
PSNR
SSIM

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Decision Sciences (miscellaneous)
Control and Optimization

Access to Document

10.1109/INES49302.2020.9147124

Fingerprint Dive into the research topics of 'Near-lossless Image Compression with Parity Reduction'. Together they form a unique fingerprint.

Cite this

Koc, B., Arnavut, Z., Voronin, S., & Kocak, H. (2020). Near-lossless Image Compression with Parity Reduction. In INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings (pp. 225-229). [9147124] (INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INES49302.2020.9147124

Near-lossless Image Compression with Parity Reduction. / Koc, Basar; Arnavut, Ziya; Voronin, Sergey; Kocak, Huseyin.

INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 225-229 9147124 (INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings).

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

Koc, B, Arnavut, Z, Voronin, S & Kocak, H 2020, Near-lossless Image Compression with Parity Reduction. in INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings., 9147124, INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 225-229, 24th IEEE International Conference on Intelligent Engineering Systems, INES 2020, Reykjavik, Iceland, 7/8/20. https://doi.org/10.1109/INES49302.2020.9147124

Koc B, Arnavut Z, Voronin S, Kocak H. Near-lossless Image Compression with Parity Reduction. In INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 225-229. 9147124. (INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings). https://doi.org/10.1109/INES49302.2020.9147124

Koc, Basar ; Arnavut, Ziya ; Voronin, Sergey ; Kocak, Huseyin. / Near-lossless Image Compression with Parity Reduction. INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 225-229 (INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings).

@inproceedings{4daa427027ae42ac99cce6b764e37cc9,

title = "Near-lossless Image Compression with Parity Reduction",

abstract = "In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set. ",

keywords = "BWIC_I, JPEG, JPEG 2000, Least significant bit, Near-lossless image compression, Parity reduction, PSNR, SSIM",

author = "Basar Koc and Ziya Arnavut and Sergey Voronin and Huseyin Kocak",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 24th IEEE International Conference on Intelligent Engineering Systems, INES 2020 ; Conference date: 08-07-2020 Through 10-07-2020",

year = "2020",

month = jul,

doi = "10.1109/INES49302.2020.9147124",

language = "English (US)",

series = "INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "225--229",

booktitle = "INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings",

}

TY - GEN

T1 - Near-lossless Image Compression with Parity Reduction

AU - Koc, Basar

AU - Arnavut, Ziya

AU - Voronin, Sergey

AU - Kocak, Huseyin

PY - 2020/7

Y1 - 2020/7

N2 - In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.

AB - In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.

KW - BWIC_I

KW - JPEG

KW - JPEG 2000

KW - Least significant bit

KW - Near-lossless image compression

KW - Parity reduction

KW - PSNR

KW - SSIM

UR - http://www.scopus.com/inward/record.url?scp=85092648234&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85092648234&partnerID=8YFLogxK

U2 - 10.1109/INES49302.2020.9147124

DO - 10.1109/INES49302.2020.9147124

M3 - Conference contribution

AN - SCOPUS:85092648234

T3 - INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings

SP - 225

EP - 229

BT - INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 24th IEEE International Conference on Intelligent Engineering Systems, INES 2020

Y2 - 8 July 2020 through 10 July 2020

ER -