A Fast Algorithm of Exponent Moments in Image Reconstruction

Wu Yu; Ping Zi-liang; Li Yin

doi:doi:10.11648/j.sd.20160405.15

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A Fast Algorithm of Exponent Moments in Image Reconstruction

Wu Yu, Ping Zi-liang, Li Yin

Published in Science Discovery (Volume 4, Issue 5)

Received: 13 October 2016 Published: 13 October 2016

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Abstract

Image moments as a very effective highly concentrated image feature differ from image simple geometric features. Using image moments as a global feather to describe image feather information is a key problem in the image information domain of image recognition, image transformation, image classification, image transmission and image compression. On the basis of exponent moments, the image can be reconstruction approximately. And the exponent moments calculation can be more fast and more accurate using 2-D Fast Fourier Transform.

Published in	Science Discovery (Volume 4, Issue 5)
DOI	10.11648/j.sd.20160405.15
Page(s)	292-296
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Radial Harmonic Fourier Moments, Exponent Moments, 2-D Fast Fourier Transform

References

[1]	孟敏，平子良.基于指数矩的图像分解和重建[J].内蒙古师范大学学报：自然科学汉文版，2011,40(03):258-260.
[2]	平子良，盛云龙.用切比雪夫图像矩描述图像[J].内蒙古师范大学学报：自然科学汉文版，2002,31(3): 216-219.
[3]	银国瑞.基于圆谐-傅里叶矩的抗几何攻击数字水印算法研究[D].内蒙古师范大学物理与电子信息学院，2009.
[4]	Jia-li Dong,Guo-ruiYin,Zi-liang Ping. Geometricallyrobust image watermarking based of Jacobi-Fouriermoments[J].Optoelectronics Letters.2009(5)
[5]	姜永静.指数矩及其在模式识别中的应用[D].北京邮电大学2011.
[6]	孟敏.基于指数矩的抗几何攻击数字图像水印[D].内蒙古师范大学,2011.
[7]	孙景峰，刘慧英，纪超，郭慧娟.高分辨率图像的指数矩描述[J].应用科学学报,2016,34(2):127-134.
[8]	PING Z L,JIANG Y J.An algorithm for computation of radial-harmonic-Fourier moments [C]//The Second International Conference on Functional Manufacturing Technologies (ICFMT2010),2010:254-288.
[9]	PING Z, JIANG Y, ZHOU S, WU Y.FFT algorithm of complex exponent moments and its application in image recognition [C]//The Sixth International Conference on Digital Image Processing. International Society for Optics and Photonics (ICDIP2014),2014:4177-4180.
[10]	杨帆等.数字图像处理与分析[M].北京：北京航空航天大学出版社，2010.

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Wu Yu, Ping Zi-liang, Li Yin. (2016). A Fast Algorithm of Exponent Moments in Image Reconstruction. Science Discovery, 4(5), 292-296. https://doi.org/10.11648/j.sd.20160405.15

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ACS Style

Wu Yu; Ping Zi-liang; Li Yin. A Fast Algorithm of Exponent Moments in Image Reconstruction. Sci. Discov. 2016, 4(5), 292-296. doi: 10.11648/j.sd.20160405.15

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AMA Style

Wu Yu, Ping Zi-liang, Li Yin. A Fast Algorithm of Exponent Moments in Image Reconstruction. Sci Discov. 2016;4(5):292-296. doi: 10.11648/j.sd.20160405.15

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@article{10.11648/j.sd.20160405.15,
  author = {Wu Yu and Ping Zi-liang and Li Yin},
  title = {A Fast Algorithm of Exponent Moments in Image Reconstruction},
  journal = {Science Discovery},
  volume = {4},
  number = {5},
  pages = {292-296},
  doi = {10.11648/j.sd.20160405.15},
  url = {https://doi.org/10.11648/j.sd.20160405.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20160405.15},
  abstract = {Image moments as a very effective highly concentrated image feature differ from image simple geometric features. Using image moments as a global feather to describe image feather information is a key problem in the image information domain of image recognition, image transformation, image classification, image transmission and image compression. On the basis of exponent moments, the image can be reconstruction approximately. And the exponent moments calculation can be more fast and more accurate using 2-D Fast Fourier Transform.},
 year = {2016}
}

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TY  - JOUR
T1  - A Fast Algorithm of Exponent Moments in Image Reconstruction
AU  - Wu Yu
AU  - Ping Zi-liang
AU  - Li Yin
Y1  - 2016/10/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sd.20160405.15
DO  - 10.11648/j.sd.20160405.15
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 292
EP  - 296
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20160405.15
AB  - Image moments as a very effective highly concentrated image feature differ from image simple geometric features. Using image moments as a global feather to describe image feather information is a key problem in the image information domain of image recognition, image transformation, image classification, image transmission and image compression. On the basis of exponent moments, the image can be reconstruction approximately. And the exponent moments calculation can be more fast and more accurate using 2-D Fast Fourier Transform.
VL  - 4
IS  - 5
ER  -

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Author Information

Wu Yu

Department of Communication and Information Engineering, Century College, Beijing University of Posts and Telecommunications,Beijing, China
Ping Zi-liang

Department of Communication and Information Engineering, Century College, Beijing University of Posts and Telecommunications,Beijing, China
Li Yin

Department of Communication and Information Engineering, Century College, Beijing University of Posts and Telecommunications,Beijing, China

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APA Style

Wu Yu, Ping Zi-liang, Li Yin. (2016). A Fast Algorithm of Exponent Moments in Image Reconstruction. Science Discovery, 4(5), 292-296. https://doi.org/10.11648/j.sd.20160405.15

Copy | Download

ACS Style

Wu Yu; Ping Zi-liang; Li Yin. A Fast Algorithm of Exponent Moments in Image Reconstruction. Sci. Discov. 2016, 4(5), 292-296. doi: 10.11648/j.sd.20160405.15

Copy | Download

AMA Style

Wu Yu, Ping Zi-liang, Li Yin. A Fast Algorithm of Exponent Moments in Image Reconstruction. Sci Discov. 2016;4(5):292-296. doi: 10.11648/j.sd.20160405.15

Copy | Download

@article{10.11648/j.sd.20160405.15,
  author = {Wu Yu and Ping Zi-liang and Li Yin},
  title = {A Fast Algorithm of Exponent Moments in Image Reconstruction},
  journal = {Science Discovery},
  volume = {4},
  number = {5},
  pages = {292-296},
  doi = {10.11648/j.sd.20160405.15},
  url = {https://doi.org/10.11648/j.sd.20160405.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sd.20160405.15},
  abstract = {Image moments as a very effective highly concentrated image feature differ from image simple geometric features. Using image moments as a global feather to describe image feather information is a key problem in the image information domain of image recognition, image transformation, image classification, image transmission and image compression. On the basis of exponent moments, the image can be reconstruction approximately. And the exponent moments calculation can be more fast and more accurate using 2-D Fast Fourier Transform.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - A Fast Algorithm of Exponent Moments in Image Reconstruction
AU  - Wu Yu
AU  - Ping Zi-liang
AU  - Li Yin
Y1  - 2016/10/13
PY  - 2016
N1  - https://doi.org/10.11648/j.sd.20160405.15
DO  - 10.11648/j.sd.20160405.15
T2  - Science Discovery
JF  - Science Discovery
JO  - Science Discovery
SP  - 292
EP  - 296
PB  - Science Publishing Group
SN  - 2331-0650
UR  - https://doi.org/10.11648/j.sd.20160405.15
AB  - Image moments as a very effective highly concentrated image feature differ from image simple geometric features. Using image moments as a global feather to describe image feather information is a key problem in the image information domain of image recognition, image transformation, image classification, image transmission and image compression. On the basis of exponent moments, the image can be reconstruction approximately. And the exponent moments calculation can be more fast and more accurate using 2-D Fast Fourier Transform.
VL  - 4
IS  - 5
ER  -

Copy | Download