高分辨率图像的指数矩描述

doi:10.3969/j.issn.0255-8297.2016.02.002

Abstract

Abstract: Based on the definition and calculation method of exponential moments, this paper describes a high-resolution image using the exponential moment matrix. Combining image segmentation and further treatment of sub-images, we use FFT to calculate the exponential moment matrix of a high-resolution image. Each sub-image is then reconstructed with the obtained exponential moment matrix. The original image is recomposed using the reconstructed sub-images. Meanwhile, based on Itti's visual attention model, SNR of the objectively interested area in the reconstructed image is analyzed. Simulation results show that the reconstructed image block effect caused by segmentation can be reduced, and SNR of the reconstructed image is improved. It is shown that describing a high-resolution image with image moment invariant matrix is feasible.

Key words: exponential moment, image normalization, image quality, image reconstruction

CLC Number:

TP311

SUN Jing-feng, LIU Hui-ying, JI Chao, GUO Hui-juan. High-Resolution Image Based on Exponent Moments[J]. Journal of Applied Sciences, 2016, 34(2): 127-134.

References

[1] Hai H P, Ping Z L, Bo W R G, Sheng Y L, Chen S Z, Wu W K. Cell image recognition with radial harmonic Fourier moments[J]. Chinese Physics Letters, 2003, 12(6):610-614.

[2] Zeng J L, Zou Y R, Du D, Chang B H, Pan J L. Research on visual weld trace detection method based on invariant moment features[M]//Robotic Welding, Intelligence and Automation. Springer International Publishing, 2015:239-248.

[3] Xiang F, Yong H, Dandan S. An image retrieval method based on Hu invariant moment and improved annular histogram[J]. Elektronika ir Elektrotechnika, 2014, 20(4):67-71.

[4] Premaratne P, Premaratne M. Image matching using moment invariants[J]. Neurocomputing, 2014, 137:65-70.

[5] Wang X Y, Li W Y, Yang H Y, Niu P P, Li Y W. Invariant quaternion radial harmonic Fourier moments for color image retrieval[J]. Optics & Laser Technology, 2015, 66:78-88.

[6] Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11):1254-1259.

[7] 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.

[8] 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.

[9] Hu H T, Zhang Y D, Shao C, Ju Q. Orthogonal moments based on exponent functions:exponent-Fourier moments[J]. Pattern Recognition, 201447(8):2596-2606.

[10] 姜永静. 指数矩及其在模式识别中的应用[D]. 北京:北京邮电大学,2011:71-73.

[11] Yang H Y, Wang X Y, Wang P, Niu P P. Geometrically resilient digital watermarking scheme based on radial harmonic Fourier moments magnitude[J]. AEU-International Journal of Electronics and Communications, 2015, 69(1):389-399.

[12] Schaefer G, Stich M. UCID:an uncompressed color image database[J]. Proceedings of SPIEthe International Society for Optical Engineering, 2004, 5307:472-480.

[13] 沈兰荪,张菁,李晓光. 图像检索与压缩域处理技术的研究[M]. 北京:人民邮电出版社,2009:40-45.

[14] Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters, 2008, 44(13):800-801.

[15] Itti L, Koch C. Computational modelling of visual attention[J]. Nature Reviews Neuroscience, 2001, 2(3):194-203.

High-Resolution Image Based on Exponent Moments

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 7

Recommended Articles

Metrics

Comments

[1]	QI Mengyu, ZHAO Lili, LIU Xin, YAN Zhuangzhi. Three-Dimensional Photoacoustic Image Reconstruction Using Weighted Alternating Direction Method [J]. Journal of Applied Sciences, 2019, 37(3): 336-348.
[2]	CAO Xin, LI Zhanming, HU Wenjin. A Method for Color Image Quality Assessment [J]. Journal of Applied Sciences, 2019, 37(3): 398-406.
[3]	FENG Xiang1,2, WAN Wang-gen1,2. Sparse Representation and Reconstruction of Image Based on Compressed Sensing [J]. Journal of Applied Sciences, 2014, 32(5): 447-452.
[4]	LI Hong-jun. No-reference Image Quality Assessment Based on Parameters of Wavelet Coefficients Distribution [J]. Journal of Applied Sciences, 2013, 31(2): 170-176.
[5]	JIN Wei, FU Ran-di, YE Ming, CEN Xiong-ying, YIN Cao-qian. Compressed Sensing Reconstruction for Satellite Cloud Images Using Residual Estimation [J]. Journal of Applied Sciences, 2011, 29(5): 495-499.
[6]	WANG Bao-yun, ZHANG Rong, YIN Dong. Spatial Pooling Strategies for Image Quality Assessment Based on Local Structural Information [J]. Journal of Applied Sciences, 2011, 29(5): 473-482.
[7]	DAI Xiu-bin;SHU Hua-zhong;LUO Li-min;Han Guo-niu;Jean Louis Coatrieux;. Image Reconstruction from Limited Range Projections Using Discrete Orthogonal Moments [J]. Journal of Applied Sciences, 2008, 26(6): 586-593 .