De-noising techniques for terahertz responses of biological samples
De-noising techniques for terahertz responses of biological samples
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DOI：
10.1016/s0026-2692(01)00093-3
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发表时间：
2001-12-01
影响因子：
2.2
通讯作者：
Abbott, D
中科院分区：
文献类型：
--
作者：
Ferguson, B;Abbott, D
可以使用信号处理技术来提高脉冲太赫兹(T-ray)成像系统的速度、分辨率和噪声稳健性。这类系统有广泛的应用，最近的兴趣集中在几个有前途的生物医学领域。在实现商业生物医学太赫兹系统之前，有许多重大挑战需要克服。最近的研究集中在实现高速、紧凑和便携的T射线成像系统上。该系统将在很大程度上利用MOEMS技术。这类系统开发的一个主要阶段是设计有效的软件算法来实时执行信号识别和成像操作。本文讨论了一些适合于从太赫兹脉冲成像系统中获得的数据中去噪和提取信息的信号处理技术。考虑了两种主要的去噪技术。将小波去噪和维纳去卷积算法应用于生物样品的太赫兹响应，包括西班牙塞拉诺火腿和橡树叶。(C)2001爱思唯尔科学有限公司。保留所有权利。
Signal processing techniques may be used to improve the speed, resolution and noise robustness of pulsed terahertz (T-ray) imaging systems. Such systems have a wide range of applications and much recent interest has focussed on several promising biomedical fields. There are a number of significant challenges to be overcome before a commercial biomedical terahertz system can be realised. Recent research is focussed on the implementation of a high speed, compact and portable T-ray imaging system. This system will draw heavily on MOEMS technology. One of the major stages in the development of such a system is the design of efficient software algorithms to perform signal recognition and imaging operations in real time.This paper considers a number of signal processing techniques suitable for de-noising and extracting information from the data obtained in a terahertz pulse imaging system. Two main de-noising techniques are considered. Wavelet de-noising and Wiener deconvolution algorithms are applied to the terahertz responses of biological samples including Spanish Serrano ham and an oak leaf. (C) 2001 Elsevier Science Ltd. All rights reserved.