Bit allocation strategy based on Psychovisual threshold in image compression

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 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Multimedia Tools and Applications Springer Journals

Bit allocation strategy based on Psychovisual threshold in image compression

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Computer Science; Multimedia Information Systems; Computer Communication Networks; Data Structures, Cryptology and Information Theory; Special Purpose and Application-Based Systems
ISSN
1380-7501
eISSN
1573-7721
D.O.I.
10.1007/s11042-017-4999-9
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Multimedia Tools and ApplicationsSpringer Journals

Published: Jul 26, 2017

References

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