Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient

It is difficult for the conventional image compression method to achieve good compression effect in the underwater acoustic image (UWAI), because the UWAI has large amount of noise and low correlation between pixel points. In this paper, fractal coding is introduced into UWAI compression, and a frac...

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Main Authors: Liu Lixin, Guo Feng, Wu Jinqiu
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/5647519
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spelling doaj-3babd9905baf45a1af2a882403da62c02020-11-24T20:49:03ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/56475195647519Underwater Acoustic Image Encoding Based on Interest Region and Correlation CoefficientLiu Lixin0Guo Feng1Wu Jinqiu2Institute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Hainan 572000, ChinaInstitute of Deep-Sea Science and Engineering, Chinese Academy of Sciences, Hainan 572000, ChinaBeijing Institute of Control And Electronic Technology, Beijing 100038, ChinaIt is difficult for the conventional image compression method to achieve good compression effect in the underwater acoustic image (UWAI), because the UWAI has large amount of noise and low correlation between pixel points. In this paper, fractal coding is introduced into UWAI compression, and a fractal coding algorithm based on interest region is proposed according to the importance of different regions in the image. The application problems of traditional quadtree segmentation in UWAIs was solved by the range block segmentation method in the coding process which segmented the interest region into small size and the noninterest region into large size and balanced the compression ratio and the decoded image quality. This paper applies the classification, reduction codebook, and correlation coefficient matching strategy to narrow the search range of the range block in order to solve the problem of the long encoding time and the calculation amount of encoding process is greatly reduced. The experimental results show that the proposed algorithm improves the compression ratio and encoding speed while ensuring the image quality of important regions in the UWAI.http://dx.doi.org/10.1155/2018/5647519
collection DOAJ
language English
format Article
sources DOAJ
author Liu Lixin
Guo Feng
Wu Jinqiu
spellingShingle Liu Lixin
Guo Feng
Wu Jinqiu
Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
Complexity
author_facet Liu Lixin
Guo Feng
Wu Jinqiu
author_sort Liu Lixin
title Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
title_short Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
title_full Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
title_fullStr Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
title_full_unstemmed Underwater Acoustic Image Encoding Based on Interest Region and Correlation Coefficient
title_sort underwater acoustic image encoding based on interest region and correlation coefficient
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2018-01-01
description It is difficult for the conventional image compression method to achieve good compression effect in the underwater acoustic image (UWAI), because the UWAI has large amount of noise and low correlation between pixel points. In this paper, fractal coding is introduced into UWAI compression, and a fractal coding algorithm based on interest region is proposed according to the importance of different regions in the image. The application problems of traditional quadtree segmentation in UWAIs was solved by the range block segmentation method in the coding process which segmented the interest region into small size and the noninterest region into large size and balanced the compression ratio and the decoded image quality. This paper applies the classification, reduction codebook, and correlation coefficient matching strategy to narrow the search range of the range block in order to solve the problem of the long encoding time and the calculation amount of encoding process is greatly reduced. The experimental results show that the proposed algorithm improves the compression ratio and encoding speed while ensuring the image quality of important regions in the UWAI.
url http://dx.doi.org/10.1155/2018/5647519
work_keys_str_mv AT liulixin underwateracousticimageencodingbasedoninterestregionandcorrelationcoefficient
AT guofeng underwateracousticimageencodingbasedoninterestregionandcorrelationcoefficient
AT wujinqiu underwateracousticimageencodingbasedoninterestregionandcorrelationcoefficient
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