Open AccessDual tree complex wavelet transform based denoising of optical microscopy images
Author(s) -
Ufuk Bal
Publication year - 2012
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.3.003231
Subject(s) - complex wavelet transform , shot noise , noise reduction , wavelet , artificial intelligence , discrete wavelet transform , wavelet transform , noise (video) , aliasing , pattern recognition (psychology) , computer science , mathematics , wavelet packet decomposition , stationary wavelet transform , algorithm , computer vision , image (mathematics) , telecommunications , detector , undersampling
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 fıber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions.