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Noise removal for medical X‐ray images in wavelet domain
Author(s) -
Wang Ling,
Lu Jianming,
Li Yeqiu,
Yahagi Takashi,
Okamoto Takahide
Publication year - 2008
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.20486
Subject(s) - wavelet , noise (video) , wavelet transform , second generation wavelet transform , preprocessor , discrete wavelet transform , computer science , shot noise , artificial intelligence , stationary wavelet transform , algorithm , mathematics , image (mathematics) , pattern recognition (psychology) , computer vision , telecommunications , detector
Abstract Many important problems in engineering and science are well‐modeled by Poisson noise, and the noise of medical X‐ray images is Poisson noise. In this paper, we propose a method for noise removal for degraded medical X‐ray images using improved preprocessing and an improved BayesShrink (IBS) method in the wavelet domain. First, we preprocess the medical X‐ray image. Second, we apply the Daubechies (db) wavelet transform to medical X‐ray images to acquire scaling and wavelet coefficients. Third, we apply the proposed IBS method to process wavelet coefficients. Finally, we compute the inverse wavelet transform for the threshold coefficients. Experimental results show that the proposed method always outperforms traditional methods. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 163(3): 37– 46, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20486