傅立叶分解法荧光层析成像

本文提出一种基于结构光照明和傅立叶分解方法的荧光层析成像技术，该技术首先将激发光的强度沿着光轴方向调制成余弦函数，然后用此激发光对样品作传统的二维扫描，在每一个扫描位置余弦函数的频率在一定的范围内扫描，同时一一对应地记录下所发出的荧光强度。只要对所纪录的荧光序列做一个简单的傅立叶变换，即可以得到此位置样品沿着光轴方向的荧光团分布。这样通过一个传统的二维扫描，就可以得到一个三维的阳样品分布。

Complex wavelets and shift invariance

Recently we have developed a new form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. This introduces limited redundancy (2 m:1 for m-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency with good well-balanced frequency responses. In this paper we analyse why the new transform can be designed to be shift invariant, and describe how to estimate the accuracy of this approximation and design suitable filters to achieve this.

AN EFFICIENT ITERATIVE DFT-BASED CHANNEL ESTIMATION FOR MIMO-OFDM SYSTEMS ON MULTIPATH CHANNELS

In this paper, an efficient iterative discrete Fourier transform (DFT) -based channel estimator with good performance for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems such as IEEE 802.11n which retain some sub-carriers as null sub-carriers (or virtual carriers) is proposed. In order to eliminate the mean-square error (MSE) floor effect existed in conventional DFT-based channel estimators, we proposed a low-complexity method to detect the significant channel impulse response (CIR) taps, which neither need any statistical channel information nor a predetermined threshold value. Analysis and simulation results show that the proposed method has much better performance than conventional DFT-based channel estimators and without MSE floor effect.

门限密码学中的离散傅里叶变换

基于离散傅里叶变换提出了一种通用的门限密码学中恢复分享秘密的算法。该算法是离散傅里叶变换在门限密码学中的首次应用。利用该算法，门限密码体制可以有效地达到鲁棒性和自适应安全性。同时，引入了设计有效的鲁棒自适应安全的门限密码体制的新的通用技术。

DCT变换域乘嵌入图像水印的检测算法

目前大多数水印算法采用线性相关的方法检测水印，但是，当原始媒体信号不服从高斯分布，或者水印不是以加嵌入方式嵌入到待保护的媒体对象中时，该方法存在一定的问题．数字水印的不可感知性约束决定了水印检测是一个弱信号检测问题，利用这一特性，首先从图像DCT（discrete cosine transfom）交流变换系数的统计特性出发，应用广义高斯分布来建立其统计分布模型，然后将水印检测问题转化为二元假设检验问题，以非高斯噪声中弱信号检测的基本理论作为乘嵌入水印的理论检测模型，推导出优化的乘嵌入水印检测算法，并对检测算法进行了实验．结果表明，对于未知嵌入强度的乘水印的盲检测，提出的水印检测器具有良好的检测性能．因此，该检测器能在数字媒体数据的版权保护方面得到了实际的应用．

地形可视性分析中观察点设置问题研究

观察点设置问题是地形可视性分析中的一类重要问题，对该问题的研究可以在空间信息辅助决策、通信、旅游、野生动物保护等领域发挥重大作用。本文在对地形可视性分析中观察点设置问题现有研究成果总结和分析基础上对该问题展开深入研究。 首先，针对现有解决方法只从智能算法或地形数据表示方法单一角度进行分析和研究的局限性，提出了一种问题相关的智能算法和数据表示方法相结合的解决问题新框架。该框架考虑了解决观察点设置问题时智能算法的优点和数据表示方式的特点相互配合问题，目的是充分发挥二者各自的优势以提高观察点设置问题解决的准确度与效率。 其次，在深入分析观察点设置问题本身特点的基础上，结合隶属云理论的基本理论和方法，对经典模拟退火算法从退温函数设计、温度产生过程、状态生成过程三方面进行了问题相关的改进，提出了一种适于观察点设置问题的改进模拟退火算法(Improved Simulated Annealing algorithm, ISA)。该算法一方面保持了经典模拟退火算法的稳定倾向特性，保证了算法满足伴随退火温度的不断下降，对恶化的新状态越来越难于接受这一模拟退火算法的最基本特征；另一方面其退火温度的连续性随机变化特性和隐含的“回火升温”过程，则有利于算法有效拒绝恶化解，加速算法收敛，能够更好地满足观察点设置问题对于算法收敛速度的要求。 再次，在分析地形数据的精度、误差等因素对观察点设置问题的解决准确性和解决效率影响程度的基础上，提出了一种基于离散余弦变换的地形数据内插方法(Discrete Cosine Transformation Interpolation method, DCTI)。新方法将传统空域上的地形内插转换到变换域上进行，同时充分利用了离散余弦变换的熵保持特性和能量压缩特性，简化了变换域上的内插过程，提高了地形数据内插的效率和精度。DCTI方法与其他现有典型地形数据内插方法相比，对地形可视性信息获取的准确性和效率影响最小，为平衡观察点设置问题解决过程中时间效率和准确度之间的关系，最终有效地解决观察点设置问题提供了数据基础。 最后，从智能算法和地形数据相结合的角度出发，提出了一种基于ISA和DCTI相结合的观察点设置问题多分辨率处理方法(Multi-Resolution Processing method, MRP)。新方法将模拟退火算法的逐次退火特点和地形数据的多分辨率表示充分结合，达到了发挥算法数据相结合的综合优势的目的。与现有单纯基于模拟退火算法的解决方法相比，在问题解决准确度保持不变的前提下，基于MRP方法的观察点设置问题解决的平均耗时减少85%~95%，为实际工程应用问题的解决提供了一条重要途径。

基于非均匀DCT的量化索引调制隐写

基于量化索引调制(QIM)的隐写技术正日益受到隐写分析的威胁。该文将通常在DCT域隐写的做法改为在非均匀DCT域进行,将参数作为密钥,提出了一种NDCT-QIM图像隐写方法。由于在攻击者猜测的域中,嵌入信号具有扩散性,NDCT-QIM方法不利于隐写分析对隐写特征的检测,分析和实验表明,它能够更好地抵御基于梯度能量、直方图及小波统计特征等常用统计量的隐写分析,增强了隐写的隐蔽性。

Local Feature Based Geometric-Resistant Image Information Hiding

Watermarking aims to hide particular information into some carrier but does not change the visual cognition of the carrier itself. Local features are good candidates to address the watermark synchronization error caused by geometric distortions and have attracted great attention for content-based image watermarking. This paper presents a novel feature point-based image watermarking scheme against geometric distortions. Scale invariant feature transform (SIFT) is first adopted to extract feature points and to generate a disk for each feature point that is invariant to translation and scaling. For each disk, orientation alignment is then performed to achieve rotation invariance. Finally, watermark is embedded in middle-frequency discrete Fourier transform (DFT) coefficients of each disk to improve the robustness against common image processing operations. Extensive experimental results and comparisons with some representative image watermarking methods confirm the excellent performance of the proposed method in robustness against various geometric distortions as well as common image processing operations.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

多尺度分解与相位反褶积提高海上地震资料分辨率和信噪比

Offshore seismic exploration is full of high investment and risk. And there are many problems, such as multiple. The technology of high resolution and high S/N ratio on marine seismic data processing is becoming an important project. In this paper, the technology of multi-scale decomposition on both prestack and poststack seismic data based on wavelet and Hilbert-Huang transform and the theory of phase deconvolution is proposed by analysis of marine seismic exploration, investigation and study of literatures, and integration of current mainstream and emerging technology. Related algorithms are studied. The Pyramid algorithm of decomposition and reconstruction had been given by the Mallat algorithm of discrete wavelet transform In this paper, it is introduced into seismic data processing, the validity is shown by test with field data. The main idea of Hilbert-Huang transform is the empirical mode decomposition with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions that admit well-behaved Hilbert transform. After the decomposition, a analytical signal is constructed by Hilbert transform, from which the instantaneous frequency and amplitude can be obtained. And then, Hilbert spectrum. This decomposition method is adaptive and highly efficient. Since the decomposition is based on the local characteristics of the time scale of data, it is applicable to nonlinear and non-stationary processes. The phenomenons of fitting overshoot and undershoot and end swings are analyzed in Hilbert-Huang transform. And these phenomenons are eliminated by effective method which is studied in the paper. The technology of multi-scale decomposition on both prestack and poststack seismic data can realize the amplitude preserved processing, enhance the seismic data resolution greatly, and overcome the problem that different frequency components can not restore amplitude properly uniformly in the conventional method. The method of phase deconvolution, which has overcome the minimum phase limitation in traditional deconvolution, approached the base fact well that the seismic wavelet is phase mixed in practical application. And a more reliable result will be given by this method. In the applied research, the high resolution relative amplitude preserved processing result has been obtained by careful analysis and research with the application of the methods mentioned above in seismic data processing in four different target areas of China Sea. Finally, a set of processing flow and method system was formed in the paper, which has been carried on in the application in the actual production process and has made the good progress and the huge economic benefit.

Wavelets for the Analysis and Compression of Power System Disturbances

Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.

Area-efficient high-speed 3D DWT processor architecture

An area-efficient high-throughput architecture based on distributed arithmetic is proposed for 3D discrete wavelet transform (DWT). The 3D DWT processor was designed in VHDL and mapped to a Xilinx Virtex-E FPGA. The processor runs up to 85 MHz, which can process the five-level DWT analysis of a 128 x 128 x 128 fMRI volume image in 20 ms.

Progressive Audio Scrambling in Compressed Domain

Audio scrambling can be employed to ensure confidentiality in audio distribution. We first describe scrambling for raw audio using the discrete wavelet transform (DWT) first and then focus on MP3 audio scrambling. We perform scrambling based on a set of keys which allows for a set of audio outputs having different qualities. During descrambling, the number of keys provided and the number of rounds of descrambling performed will decide the audio output quality. We also perform scrambling by using multiple keys on the MP3 audio format. With a subset of keys, we can descramble to obtain a low quality audio. However, we can obtain the original quality audio by using all of the keys. Our experiments show that the proposed algorithms are effective, fast, simple to implement while providing flexible control over the progressive quality of the audio output. The security level provided by the scheme is sufficient for protecting MP3 music content.

Bimodal biometric verification based on face and lips

In this paper, we present a novel approach to person verification by fusing face and lip features. Specifically, the face is modeled by the discriminative common vector and the discrete wavelet transform. Our lip features are simple geometric features based on a lip contour, which can be interpreted as multiple spatial widths and heights from a center of mass. In order to combine these features, we consider two simple fusion strategies: data fusion before training and score fusion after training, working with two different face databases. Fusing them together boosts the performance to achieve an equal error rate as low as 0.4% and 0.28%, respectively, confirming that our approach of fusing lips and face is effective and promising.

Protection Assessment using Reduced Power System Fault Data

Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for the compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the compression properties of the discrete wavelet transform using actual power system data. The results presented in the paper indicate that reduction ratios up to 10:1 with acceptable distortion are achievable. The paper discusses the application of the reduction method for expedient fault analysis and protection assessment.