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The remote sensing image enhancement based on nonsubsampled contourlet transform and unsharp masking
Author(s) -
Pu Xiaoting,
Jia Zhenhong,
Wang Liejun,
Hu Yingjie,
Yang Jie
Publication year - 2013
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.3041
Subject(s) - unsharp masking , contourlet , masking (illustration) , gibbs phenomenon , image (mathematics) , standard deviation , artificial intelligence , sharpening , computer science , computer vision , pattern recognition (psychology) , mathematics , image enhancement , statistics , wavelet transform , fourier transform , mathematical analysis , art , visual arts , wavelet
SUMMARY To restrain pseudo‐Gibbs phenomenon, low contrast and blurred phenomenon in the process of image enhancement, a new method based on the nonsubsampled contourlet transform and the unsharp masking is proposed in this paper. The proposed method utilizes the shift‐invariance of nonsubsampled contourlet transform to restrain the pseudo‐Gibbs phenomenon, and then enhance details of the image by unsharp masking. We achieved an increase in image definition by 54.5%, the mean increased by 15.6%, whereas the standard deviation increased by 54.5% compared with the unsharp masking method. To the noisy image, we achieved an increase in image definition by 35.4%, the mean increased by 2.2%, whereas the standard deviation increased by 34.9% compared with the unsharp masking method. Copyright © 2013 John Wiley & Sons, Ltd.