Puvanathasan Prabakar, Bizheva Kostadinka
Opt Express. 2007 Nov 26;15(24):15747-58. doi: 10.1364/oe.15.015747.
A novel speckle reduction technique based on soft thresholding of wavelet coefficients using interval type II fuzzy system was developed for reducing speckle noise in Optical Coherence Tomography images. The proposed algorithm is an extension of a recently published method for filtering additive Gaussian noise by use of type I fuzzy system. Unlike type I, interval type II fuzzy based thresholding filter considers the uncertainty in the calculated threshold and the wavelet coefficient is adjusted based on this uncertainty. A single parameter controls the signal-to-noise (SNR) improvement. Application of this novel algorithm to optical coherence tomograms acquired in-vivo from a human finger tip show reduction in the speckle noise with little edge blurring and image SNR improvement of about 10dB. Comparison with adaptive Wiener and adaptive Lee filters, applied to the same image, demonstrated the superior performance of the fuzzy type II algorithm in terms of image metrics improvement.
为了减少光学相干断层扫描（Optical Coherence Tomography，OCT）图像中的散斑噪声，开发了一种基于区间二型模糊系统对小波系数进行软阈值处理的新型散斑减少技术。所提出的算法是最近发表的一种利用一型模糊系统滤波加性高斯噪声方法的扩展。与一型不同，基于区间二型模糊的阈值滤波器考虑了计算阈值中的不确定性，并基于此不确定性调整小波系数。单个参数控制信噪比（SNR）的提高。将这种新算法应用于从人体指尖采集的体内光学相干断层图像，结果表明散斑噪声减少，边缘模糊很少，图像信噪比提高约10dB。与应用于同一图像的自适应维纳滤波器和自适应李滤波器相比，二型模糊算法在图像指标改善方面表现出优越的性能。
