An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold

One of the main part of image compression is a quantization process which give a significant effect to the compression performance. However, image compression based on the quantization produces blocking effect or artifact image. This research proposes a novel bit allocation strategy which assigning...

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Main Authors:	Ernawan, Ferda, Zuriani, Mustaffa, Bayuaji, Luhur
Format:	Article
Language:	English
Published:	International Information Institute Ltd. 2016
Subjects:	Q Science (General) T Technology (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/13071/ http://umpir.ump.edu.my/id/eprint/13071/ http://umpir.ump.edu.my/id/eprint/13071/1/visiogame_manuscript.pdf

id	ump-13071
recordtype	eprints
spelling	ump-130712018-02-26T01:56:16Z http://umpir.ump.edu.my/id/eprint/13071/ An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold Ernawan, Ferda Zuriani, Mustaffa Bayuaji, Luhur Q Science (General) T Technology (General) One of the main part of image compression is a quantization process which give a significant effect to the compression performance. However, image compression based on the quantization produces blocking effect or artifact image. This research proposes a novel bit allocation strategy which assigning an optimal budget of bits in image compression. The bit allocation is proposed to replace the role of the quantization process in image compression. The principle of psychovisual threshold is adopted to develop bit allocation strategy in the image compression. This quantitative research measures the optimal bit of image signals and manages the image quality level. The experimental results show the efficiency of the proposed bit allocation strategy, and that the proposed bit allocation can achieve the almost same compression rate performance while can significantly produces high quality image texture. When compared to JPEG compression, the image compression using bit allocation achieves bit rate savings of up to 4%. The quality image output provides minimum errors of artifact image. The quality image reconstruction improvement is up to 14% and the error reconstruction is reduced by up to 37%. Key Words: Bit allocation, Quantization table, Psychovisual threshold, Image compression International Information Institute Ltd. 2016-04-23 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/13071/1/visiogame_manuscript.pdf Ernawan, Ferda and Zuriani, Mustaffa and Bayuaji, Luhur (2016) An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold. Information (Japan), 19 (9B). pp. 4177-4182. ISSN 1343-4500 http://www.information-iii.org/abs_e2.html#No9(B)-2016
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	Q Science (General) T Technology (General)
spellingShingle	Q Science (General) T Technology (General) Ernawan, Ferda Zuriani, Mustaffa Bayuaji, Luhur An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
description	One of the main part of image compression is a quantization process which give a significant effect to the compression performance. However, image compression based on the quantization produces blocking effect or artifact image. This research proposes a novel bit allocation strategy which assigning an optimal budget of bits in image compression. The bit allocation is proposed to replace the role of the quantization process in image compression. The principle of psychovisual threshold is adopted to develop bit allocation strategy in the image compression. This quantitative research measures the optimal bit of image signals and manages the image quality level. The experimental results show the efficiency of the proposed bit allocation strategy, and that the proposed bit allocation can achieve the almost same compression rate performance while can significantly produces high quality image texture. When compared to JPEG compression, the image compression using bit allocation achieves bit rate savings of up to 4%. The quality image output provides minimum errors of artifact image. The quality image reconstruction improvement is up to 14% and the error reconstruction is reduced by up to 37%. Key Words: Bit allocation, Quantization table, Psychovisual threshold, Image compression
format	Article
author	Ernawan, Ferda Zuriani, Mustaffa Bayuaji, Luhur
author_facet	Ernawan, Ferda Zuriani, Mustaffa Bayuaji, Luhur
author_sort	Ernawan, Ferda
title	An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
title_short	An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
title_full	An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
title_fullStr	An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
title_full_unstemmed	An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold
title_sort	efficient image compression using bit allocation based on psychovisual threshold
publisher	International Information Institute Ltd.
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/13071/ http://umpir.ump.edu.my/id/eprint/13071/ http://umpir.ump.edu.my/id/eprint/13071/1/visiogame_manuscript.pdf
first_indexed	2023-09-18T22:15:16Z
last_indexed	2023-09-18T22:15:16Z
_version_	1777415295013486592

An Efficient Image Compression Using Bit Allocation based on Psychovisual Threshold

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