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Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression

Image compression leads to minimize the storage-requirement of an image by reducing the size of the image. This paper presents a bit allocation strategy based on psychovisual threshold in image compression considering a similar idea of audio coding. In the audio coding, a dynamic bit allocation to e...

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Main Authors: Ernawan, Ferda, M. Nomani, Kabir, Jasni, Mohamad Zain
Format: Article
Language:English
Published: Springer US 2017
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/18294/1/10.1007%252Fs11042-017-4999-9.pdf
http://umpir.ump.edu.my/id/eprint/18294/
https://doi.org/10.1007/s11042-017-4999-9
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spelling my.ump.umpir.182942018-09-25T08:38:00Z http://umpir.ump.edu.my/id/eprint/18294/ Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression Ernawan, Ferda M. Nomani, Kabir Jasni, Mohamad Zain QA75 Electronic computers. Computer science Image compression leads to minimize the storage-requirement of an image by reducing the size of the image. This paper presents a bit allocation strategy based on psychovisual threshold in image compression considering a similar idea of audio coding. In the audio coding, a dynamic bit allocation to each signal is related to the concept of variable block coding and bit allocation is performed on either a short block or long block of sample signals. Similarity, in our technique, more bits are assigned to a local block with visually-significant low frequency order, and fewer, with visually-insignificant high frequency order. This paper presents a bit allocation strategy based on psychovisual threshold in image compression. A psychovisual threshold is developed by minimizing the visual impact on the image quality degradation in image frequency coding. This paper investigates the error generated by the discrete cosine transform and sets the maximum acceptable error as a psychovisual threshold. The average reconstruction error per pixel on frequency order is utilized to prescribe a set of bit allocations which provide a significant improvement on the quality of image reconstruction at relatively low bit rates. The experimental results show that our dynamic bit-allocation technique in image compression manages to overcome artifact images in the image output. The proposed bit allocation strategy improves the quality of image reconstruction by about 20% compared to JPEG compression. This bit allocation strategy is designed to replace the traditional role of the quantization process in image compression. Springer US 2017-07-26 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/18294/1/10.1007%252Fs11042-017-4999-9.pdf Ernawan, Ferda and M. Nomani, Kabir and Jasni, Mohamad Zain (2017) Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression. Multimedia Tools and Applications. pp. 1-24. ISSN 1380-7501(print); 1573-7721(online) https://doi.org/10.1007/s11042-017-4999-9 DOI 10.1007/s11042-017-4999-9
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Ernawan, Ferda
M. Nomani, Kabir
Jasni, Mohamad Zain
Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
description Image compression leads to minimize the storage-requirement of an image by reducing the size of the image. This paper presents a bit allocation strategy based on psychovisual threshold in image compression considering a similar idea of audio coding. In the audio coding, a dynamic bit allocation to each signal is related to the concept of variable block coding and bit allocation is performed on either a short block or long block of sample signals. Similarity, in our technique, more bits are assigned to a local block with visually-significant low frequency order, and fewer, with visually-insignificant high frequency order. This paper presents a bit allocation strategy based on psychovisual threshold in image compression. A psychovisual threshold is developed by minimizing the visual impact on the image quality degradation in image frequency coding. This paper investigates the error generated by the discrete cosine transform and sets the maximum acceptable error as a psychovisual threshold. The average reconstruction error per pixel on frequency order is utilized to prescribe a set of bit allocations which provide a significant improvement on the quality of image reconstruction at relatively low bit rates. The experimental results show that our dynamic bit-allocation technique in image compression manages to overcome artifact images in the image output. The proposed bit allocation strategy improves the quality of image reconstruction by about 20% compared to JPEG compression. This bit allocation strategy is designed to replace the traditional role of the quantization process in image compression.
format Article
author Ernawan, Ferda
M. Nomani, Kabir
Jasni, Mohamad Zain
author_facet Ernawan, Ferda
M. Nomani, Kabir
Jasni, Mohamad Zain
author_sort Ernawan, Ferda
title Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
title_short Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
title_full Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
title_fullStr Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
title_full_unstemmed Bit Allocation Strategy Based on Psychovisual Threshold in Image Compression
title_sort bit allocation strategy based on psychovisual threshold in image compression
publisher Springer US
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/18294/1/10.1007%252Fs11042-017-4999-9.pdf
http://umpir.ump.edu.my/id/eprint/18294/
https://doi.org/10.1007/s11042-017-4999-9
_version_ 1643668408933285888
score 13.211869

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