Systematic examination of the geomagnetic storm sudden commencement using multi resolution analysis

Geomagnetic storm sudden commencements (SSC) contain a wealth of information which is useful in many applications. It is important to point out that the SSCs used in this study are sampled at the rate of one sample per second in order get use of such high resolution data. In this paper, two studies are made on the geomagnetic SSC and an SSC onset automatic detection algorithm is introduced. The first study is about finding the relationship between the SSC rise time and its amplitude. Where it is found that there is a positive correlation between the amplitude and the amplitude gradient which is the amplitude divided by rise time. The second study is checking the spectrum of the SSC, starting from its onset until the end of the SSC rise time. This check had proved that the SSC contains both low and high frequency regions. This led us to introduce a new term, namely the SSC variation rate (VR). This VR is defined as the maximum rate of change of the field in the higher-frequency region of the SSC. These two studies were the guide to build an SSC automatic detector of one sample per second data using multi resolution analysis (MRA) of the discrete wavelet transform (DWT). The data set contains 134 SSCs with different VRs that were collected from the Circum-pan Pacific Magnetometer Network (CPMN). It is found that the standard deviation of the detection error is 41 s and that the average error is 9 s. From the calculated error distribution function, it is found that the detection error is within the range of −1.5 to 3 min. The detection process, as will be shown in the article, takes 70 s for one station and 3 min if the decision is related to the detection(s) of other stations. These results demonstrate the superiority of the proposed algorithm over other algorithms in which the detection error ranges between −8 and 5 min and the detection process takes 2–10 min. In addition to being faster and more accurate than the other algorithms, the proposed algorithm is the first algorithm that automatically detects the SSC onset times from high-resolution data unlike previous studies that focused on determining the SSC times automatically using one-minute resolution data.     

一种自适应的DWT域数字视频水印算法

提出一种基于小波变换域的自适应视频水印算法。算法先对视频信息进行场景分割,然后从各场景中选取待插入水印的帧序列,对各帧图象进行3D—DWT,并对低频子带进行小波块的划分,据小波块的分类结果自适应地调整嵌入水印的强度。     

基于混沌加密的盲音频水印算法

将混沌理论引入到音频水印系统的研究中，设计了一种包含版权信息和密钥的二值图像作为水印，利用混沌序列将其加密后嵌入到原始音频信号的DWT域中。该水印方案包含的版权信息量大，且具有双重的安全性，很难提取出水印信号；即使提取出水印信号，如果不知道密钥，也很难恢复出原始水印图像。本算法采用了量化方法嵌入水印，提取水印时不需要原始的音频信号，实现了水印的盲提取。对一般的信号处理进行了试验，水印具有很强的鲁棒性。     

基于小波神经网络的直升机主减速器故障诊断系统

应用离散小波变换(DWT)和神经网络相结合构建直升机主减速器速器故障诊断系统: DWT对振动信号进行特征提取,神经网络对故障进行辨识和分类。阐述了DWT、帕塞瓦尔定理和广义回归神经网络(GRNN)基本理论,提出了直升机主减速器的故障诊断系统流程图,最后用某型直升机飞行时主减速器上的振动数据对该系统进行验证。实验使用了BPNN(back-propagation neural network)和GRNN两种神经网络,结果表明:提出的故障诊断系统能对主减速器故障进行较好的辨识和分类,这将为直升机主减速器故障诊断系统的进一步开发提供新的技术参考。      

一种基于纹理特性的自适应彩色图像水印方法

根据人眼的视觉系统特性,结合二维离散小波变换的多分辨率分析特性,纹理特性,提出一种小波零树结构的自适应彩色图像水印嵌入算法。该算法精选小波零树,对重要小波系数进行分类。并根据人类视觉特性和纹理特性,对不同类采用不同的嵌入方法。实验结果表明:该文提出的算法有较强的抵抗JPEG压缩攻击能力,并且对噪声、滤波、剪切等图像处理操作也取得了良好的鲁棒性。     

基于低冗余度的传感器故障诊断研究

对于大型飞机来说,飞行控制系统各部件(包括传感器)多采用高余度的硬件配置来提高系统的任务可靠性,但对小型飞机来说,由于受重量、空间及费用等原因的影响,一些传感器不适合安装三余度或四余度传感器。对于二余度或单传感器来说,如何鉴别故障传感器或判断传感器是否发生故障较为困难。同样,传统的故障诊断与隔离方法并不能隔离三余度传感器系统中的多个故障。为了解决低冗余度传感器故障诊断问题,提出一种不依赖数学模型的奇偶方程方法与小波分析相结合的传感器故障诊断方法。     

New method of enhancement using wavelet transforms applied to SODISM telescope

PICARD is a space-based observatory hosting the Solar Diameter Imager and Surface Mapper (SODISM) telescope, which has continuously observed the Sun from July 2010 and up to March 2014. In order to study the fine structure of the solar surface, it is helpful to apply techniques that enhance the images so as to improve the visibility of solar features such as sunspots or faculae. The objective of this work is to develop an innovative technique to enhance the quality of the SODISM images in the five wavelengths monitored by the telescope at 215.0?nm, 393.37?nm, 535.7?nm, 607.1?nm and 782.2?nm. An enhancement technique using interpolation of the high-frequency sub-bands obtained by Discrete Wavelet Transforms (DWT) and the input image is applied to the SODISM images. The input images are decomposed by the DWT as well as Stationary Wavelet Transform (SWT) into four separate sub-bands in horizontal and vertical directions namely, low-low (LL), low–high (LH), high-low (HL) and high–high (HH) frequencies. The DWT high frequency sub-bands are interpolated by a factor 2. The estimated high frequency sub-bands (edges) are enhanced by introducing an intermediate stage using a Stationary Wavelet Transform (SWT), and then all these sub-bands and input image are combined and interpolated with half of the interpolation factor α/2, used to interpolate the high-frequency sub-bands, in order to reach the required size for IDWT processing. Quantitative and visual results show the superiority of the proposed technique over a bicubic image resolution enhancement technique. In addition, filling factors for sunspots are calculated from SODISM images and results are presented in this work.     

基于离散小波变换的航迹关联算法研究

本文基于1-D离散小波变换(DWT)提出了一种航迹-航迹关联算法。由于目标航迹数据是非平稳随机序列,因此采用离散小波变换方法分析,利用基于F分布的假设检验模型来描述小波分解高频小波空间与低频尺度空间能量的比率,结合"去相关"方法分别讨论了航迹相关与无关的情形,并给出了一种仿真方法。仿真结果表明算法的有效性和在分辨两条相近航迹方面的优越性。     

CCSDS基于小波变换的图像压缩

通过分析一种CCSDS建议的基于小波变换的图像数据压缩的基本原理、编解码方法、系统实现和压缩性能,初步研究深空通信对于图像压缩的特殊要求。通过与现在流行的基于小波变换的图像压缩算法JPEG2000进行比较发现, CCSDS推荐的算法的性能与JPEG2000基本相当,且同样支持无损和有损压缩及渐进传输,但其算法复杂度更低,包丢失不会造成图像大面积损坏,因而更适合于深空通信。