Dual tree complex wavelet transform based denoising of optical microscopy images

被引:26
|
作者
Bal, Ufuk [1 ]
机构
[1] Mugla Sitki Kocman Univ, Fac Technol, TR-48000 Kotekli Mugla, Turkey
来源
BIOMEDICAL OPTICS EXPRESS | 2012年 / 3卷 / 12期
关键词
D O I
10.1364/BOE.3.003231
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Photon shot noise is the main noise source of optical microscopy images and can be modeled by a Poisson process. Several discrete wavelet transform based methods have been proposed in the literature for denoising images corrupted by Poisson noise. However, the discrete wavelet transform (DWT) has disadvantages such as shift variance, aliasing, and lack of directional selectivity. To overcome these problems, a dual tree complex wavelet transform is used in our proposed denoising algorithm. Our denoising algorithm is based on the assumption that for the Poisson noise case threshold values for wavelet coefficients can be estimated from the approximation coefficients. Our proposed method was compared with one of the state of the art denoising algorithms. Better results were obtained by using the proposed algorithm in terms of image quality metrics. Furthermore, the contrast enhancement effect of the proposed method on collagen fiber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions. (C) 2012 Optical Society of America
引用
收藏
页码:3231 / 3239
页数:9
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