基于人眼视觉的任意形状区域丢失图像信息重建

任意形状区域丢失图像信息的重建对于图像中遮挡区域的去除、受损图像的复原和红外图像中的目标检测具有十分重要的意义。目前普遍采用的插值重建等方法存在重建后图像的主观视觉质量明显下降的不足。因此提出了基于人眼视觉特性的任意形状区域丢失图像信息的重建模型。利用重建区域外接矩形中余留的已知信息 ,并根据人眼的低通视觉特性 ,以加权最小二乘的方式在DCT域中重建相应的DCT系数 ,然后通过IDCT得到重建后的图像。实验证明 ,通过该方法所得到的任意形状区域的重建图像 ,在主观和客观质量方面都有显著的提高。     

海流扰动下无人水下航行器的动态面反演轨迹跟踪控制

针对存在未知海流扰动条件下无人水下航行器(unmanned underwater vehicle, UUV)的轨迹跟踪控制问题, 提出一种欠驱动UUV的动态面反演轨迹跟踪控制方法。首先, 设计一种改进型海流扰动观测器来估测航行器动力学模型中存在的未知海流扰动。然后, 采用反演法并结合动态面控制技术设计三维轨迹跟踪控制器, 将控制算法中微分运算转换为简单且易于实现的代数运算, 降低控制算法复杂性的同时避免“微分爆炸”问题, 结合李雅普诺夫理论证明系统闭环稳定性。最后, 对所设计的控制器进行仿真验证, 结果表明所设计观测器能够有效应对时变海流干扰问题, 精确地完成UUV的轨迹跟踪控制任务。     

提升类小波变换加速的模基参数估计算法

将提升类小波变换(lifting wavelet-like transform, LWLT)应用于矩量法（method of moment, MOM）快速求解电场积分方程（electric field integral equation, EFIE）,对生成的稀疏化线性系统采用模基参数估计（model based parameter estimation, MBPE）算法求解,可获得小波域的宽带解,结合小波逆变换,最终实现目标电磁散射特性的宽频分析。通过不同三维散射体的计算分析,验证了算法的正确性。与传统模基参数估计算法相比,所提算法在计算时间和内存耗费上均有很大改善。     

正弦调频干扰下二进制偏移载波的精确捕获

针对正弦调频(sinusoidal frequency modulation, SFM)干扰下二进制偏移载波(binary offset carrier, BOC)信号捕获困难的问题,提出了一种基于离散SFM变换(discrete SFM transform, DSFMT)和部分匹配滤波结合全相位快速傅里叶变换(partial matched filter-all phase fast Fourier transform, PMF-apFFT)的干扰抑制捕获改进算法。该算法首先通过FFT估计SFM干扰的调制频率,在调制频率估计的基础上进行DSFMT,然后从DSFMT域中去除干扰成分再做DSFM反变换(inverse DSFMT, IDSFMT)实现干扰抑制,最后对干扰抑制后的BOC信号采用PMF-apFFT方法完成精确捕获。理论分析与仿真结果表明,所提算法在不影响DSFMT性能的前提下大幅简化了传统DSFMT的计算复杂度,并且在同等情况下,当检测概率为1时,所提算法的性能相比于DSFMT结合PMF-FFT的算法提高了大约3 dB。     

正弦调频干扰下二进制偏移载波的精确捕获

针对正弦调频(sinusoidal frequency modulation, SFM)干扰下二进制偏移载波(binary offset carrier, BOC)信号捕获困难的问题,提出了一种基于离散SFM变换(discrete SFM transform, DSFMT)和部分匹配滤波结合全相位快速傅里叶变换(partial matched filter-all phase fast Fourier transform, PMF-apFFT)的干扰抑制捕获改进算法。该算法首先通过FFT估计SFM干扰的调制频率,在调制频率估计的基础上进行DSFMT,然后从DSFMT域中去除干扰成分再做DSFM反变换(inverse DSFMT, IDSFMT)实现干扰抑制,最后对干扰抑制后的BOC信号采用PMF-apFFT方法完成精确捕获。理论分析与仿真结果表明,所提算法在不影响DSFMT性能的前提下大幅简化了传统DSFMT的计算复杂度,并且在同等情况下,当检测概率为1时,所提算法的性能相比于DSFMT结合PMF-FFT的算法提高了大约3 dB。     

基于多小波的SAR图像去噪与压缩

SAR图像固有的乘性相干斑噪声降低了图像的相关性,增加了信息熵,影响了图像压缩的性能.多小波能够同时拥有正交性、紧支性和对称性,比单小波具有更多的自由度.因此提出了在多小波域进行去噪和压缩相结合的SAR图像编码算法.首先对图像进行多小波变换,采用改进的软阈值法抑制相干斑噪声同时对图像边缘进行保护,再对多小波系数重排建立空间方向树,然后采用多级树集合划分(SPIHT)算法进行编码.实验结果表明,该算法改进了重建SAR图像的PSNR,同时对相干斑噪声进行了有效的抑制.     

矢量维数分割量化的超光谱图像压缩方法

提出了一种矢量维数分割量化的超光谱图像压缩算法,通过维数分割将矢量分为几个部分,然后利用哈达玛变换的性质,在哈达玛域内单独设计每个部分的码书。设计过程中采用最优矢量量化器设计原则,并结合分步判断排除不等式算法与LBG（Linde Bazo Gray）聚类算法快速生成矢量量化过程的最终码书,使各个部分的码书性能达到最优,改善整体码书的性能。实验表明,这种算法在码书尺寸相同的情况下,图像的恢复质量以及复杂度都优于其他几种算法。     

Tunable-Q contourlet transform for image representation

A novel tunable-quality-factor (tunable-Q) contourlet transform for geometric image representation is proposed. The Laplacian pyramid in original contourlet decomposes a signal into channels that have the same bandwidth on a logarithmic scale, and is not suitable for images with different behavior in frequency domain. We employ a new tunable-Q decomposition defined in the frequency domain by which one can flexibly tune the bandwidth of decomposition channels. With an acceptable redundancy, this tunable-Q contourlet is also anti-aliasing and its basis is sharply localized in the desired area of frequency and spatial domain. Our experiments in nonlinear approximation and denoising show that the contourlet using a better-suitable quality factor can achieve a more promising performance and often outperform wavelets and the previous contourlets both in visual quality and in terms of peak signal-to-noise ratio.     

基于场景语义的图像检索新方法

针对图像的场景语义检索问题,提出一种基于多示例学习(multi-instance learning, MIL)的新方法。首先,该方法将图像当作多示例包,再根据图像的颜色复杂度,设计了自适应JESG图像分割方法,对图像进行自动分割,并提取每个分割区域的颜色－纹理特征,当作包中的示例,将图像检索问题转化成多示例学习问题;然后,利用改进的推土机距离（earth mover distance, EMD）来度量不同多示例包（图像）之间的整体相似度,设计了一种新的惰性MIL算法,用于场景图像检索。基于COREL图像库的对比实验结果表明,设计的示例构造方法与MIL算法都是有效的,且检索精度优于其他同类方法。     

二值文本数字水印技术的研究与仿真

针对二值文本纹理复杂、信息隐藏的免疫力差的特点,提出了一种基于DCTDWT的二值文本频率域数字水印算法。算法结合了DCT和DWT二者的特点,将水印信号进行分块DCT变换,按照从低频到高频的顺序对各块系数进行重新排列,对应嵌入到原始图像的DWT分解子带中,强化了不可见性。为了验证算法的鲁棒性和不可见性,利用相似度原理设计了水印提取检测器,通过将嵌入水印后的图像进行JPEG压缩、加入高斯噪声、椒盐噪声以及将其剪切掉一块的方法来模仿图像在实际网络环境下可能遭受的各种攻击和干扰,仿真实验证明,在各种情况下,检测器均有较好的检测效果。     

Spectral matching algorithm based on nonsubsampled contourlet transform and scale-invariant feature transform

A new spectral matching algorithm is proposed by using nonsubsampled contourlet transform and scale-invariant feature transform.The nonsubsampled contourlet transform is used to decompose an image into...     

基于空间预处理联合稀疏表示高光谱图像分类

针对高光谱图像分类时光谱信息和空间信息利用不充分、分类精度低的情况, 提出一种结合空间预处理的联合稀疏表示分类方法。一方面能够弥补联合稀疏表示固定窗口模式中空间信息利用不充分的问题, 另一方面也避免了像元多次参与联合稀疏模型的构建过程。考虑每个像元对联合稀疏模型的贡献不同, 通过赋予邻域像元相应权重以提高稀疏重构精度。最后, 充分利用训练样本的已知信息修正分类结果, 在Pavia University和AVIRIS Salinas两个数据集上进行实验验证。实验结果表明, 所提方法能够有效地提高高光谱图像分类精度。     

改进的可见光通信系统SLM峰均比抑制方法

针对光正交频分复用(optical orthogonal frequency division multiplexing,O-OFDM)技术系统中高峰均比和高计算复杂度的缺点,采用选择映射(selected mapping,SLM)方法,并结合离散余弦变换(discrete cosine transform,DCT)和快速傅里叶逆变换线性特性的优势,提出了一种改进的SLM峰均比抑制方案——DCT-ISLM方法。通过计算,结果表明该DCT ISLM方法相较于传统SLM方法的峰均比降低了约3.5 dB;且随着备选信号个数的增加,系统的复杂度也得到了有效的改善。将该方法应用于传统的O-OFDM可见光通信系统中,误码性能也优于传统的SLM方案,可进一步提升此方法的实用价值。     

基于NSST域灰度关联分析的多聚焦图像融合方法

根据多聚焦图像的成像特点,并利用非下采样剪切波变换(non-subsample shearlet transform,NSST)在图像融合领域的优势,将非下采样剪切波变换运用于多聚焦图像融合.由于NSST会将图像分解为一幅低频图像和若干幅高频图像,对于低频图像采用了基于标准差的融合策略,而针对高频图像的特点,利用灰度关联分析在图像融合中的优势,将其运用在高频图像的融合中.后将低频图像和高频图像的融合图像进行NSST的逆变换后得到了融合图像.计算机仿真实验表明:相比于传统的剪切波交换,本文提出的图像融合方法提高图像的融合质量,增加了图像的信息量,具有一定的有效性和实用性.     

基于广义近似消息传递的快速DOA估计方法

针对稀疏恢复类波达方向(direction of arrival, DOA)估计算法中计算复杂度高的问题, 提出了一种基于广义近似消息传递(generalized approximate message passing, GAMP)方法的稀疏贝叶斯学习算法。该算法在现有双基地无源雷达系统模型基础上, 构建了多快拍下的GAMP信号统计模型, 将高维联合后验概率密度的计算简化为标量运算, 提高了算法的计算效率。对于离网目标, 利用梯度下降方法推导了角度空间网格更新策略, 进一步提高了角度估计的精度。仿真结果表明, 该算法在有限快拍、低信噪比情况下, 估计精度较高, 计算复杂度较低, 适用于实时性要求高的应用场景。     

Smoothing Non-Stationary Time Series Using the Discrete Cosine Transform

This paper considers the problem of smoothing a non-stationary time series (having either deterministic and/or stochastic trends) using the discrete cosine transform (DCT). The DCT is a powerful tool which has found fruitful applications in filtering and smoothing as it can closely approximate the optimal Karhunen-Loeve transform (KLT). In fact, it is known that it almost corresponds to the KLT for first-order autoregressive processes with a root close to unity: This is the case with most economic and financial time series. A number of new results are derived in the paper: (a) The explicit form of the linear smoother based on the DCT, which is found to have time-varying weights and that uses all observations; (b) the extrapolation of the DCT-smoothed series; (c) the form of the average frequency response function, which is shown to approximate the frequency response of the ideal low pass filter; (d) the asymptotic distribution of the DCT coefficients under the assumptions of deterministic or stochastic trends; (e) two news method for selecting an appropriate degree of smoothing, in general and under the assumptions in (d). These findings are applied and illustrated using several real world economic and financial time series. The results indicate that the DCT-based smoother that is proposed can find many useful applications in economic and financial time series.     

基于移不变二维混合变换的机场雷达噪声抑制

机场跑道异物(foreign object debris, FOD)检测对飞行器的安全起降有着非常重要的意义,而机场跑道异物检测的一个关键环节是很好地抑制机场雷达图像的噪声,因此提出一种基于距离时间维的移不变混合变换以抑制机场雷达图像的噪声。首先,在雷达成像时进行离散傅里叶变换(discrete Fourier transform, DFT)和维纳滤波滤除距离维上的噪声。然后,在雷达成像时进行超分析离散小波变换(hyperanalytic wavelet transform, HWT)自适应滤波去除时间维上的噪声。与传统的成像后去噪算法相比,本文的算法可以有效地去除机场雷达图像噪声,显著地改善图像的视觉效果。最重要的是该算法具有很强的实时性,可以很好地应用到工程实践中。     

Rate-distortion weighted SPIHT algorithm for interferometer data processing

As one of the next generation imaging spectrometers,the interferential spectrometer (IS) possesses the advantages of high throughput,multi-channel and great resolution.The data of IS are produced in the spatial domain,but optical applications are in the Fourier domain.Traditional compression methods can only protect the visual quality of interferometer data in the spatial domain but ignore the distortion in the Fourier domain.The relation between the distortion in the Fourier domain and the compression in the spatial domain is analyzed.By mathematical proof and validation with experiments,the relation between spatial and Fourier domains is discovered,and the significance in the Fourier domain is more important as optical path difference (OPD) increasing in the spatial domain.Based on this relation,a novel coding scheme is proposed,which can compress data in the spatial domain while reducing the distortion in the Fourier domain.In this scheme,the bit stream of the set partitioning in hierarchical trees (SPIHT) is truncated by adaptively lifting rate-distortion slopes according to the priorities of OPD based on rate-distortion optimization theory.Experimental results show that the proposed method can provide better protection of spectrum curves in the Fourier domain while maintaining a comparable visual quality in the spatial domain.     

Design and simulation of digital channelized receivers in fractional Fourier domain

An approach is proposed to realize a digital channelized receiver in the fractional Fourier domain (FRFD) for signal intercept applications. The presented architecture can be considered as a generalization of that in the traditional Fourier domain. Since the linear frequency modulation (LFM) signal has a good energy concentration in the FRFD, by choosing an appropriate fractional Fourier transform (FRFT) order, the presented architecture can concentrate the broadband LFM signal into only one sub-channel and that will prevent it from crossing several sub-channels. Thus the performance of the signal detection and parameter estimation after the sub-channel output will be improved significantly. The computational complexity is reduced enormously due to the implementation of the polyphase filter bank decomposition, thus the proposed architecture can be realized as efficiently as in the Fourier domain. The related simulation results are presented to verify the validity of the theories and methods involved in this paper.     

非凸运动辅助低秩稀疏分解目标检测算法

针对传统低秩稀疏分解(low rank and sparse decomposition, LRSD)用于视频运动目标检测时检测精度较低的问题,提出了一种鲁棒非凸运动辅助LRSD(robust nonconvex motion-assisted LRSD, RNMALRSD)的运动目标检测算法。该算法首先考虑到视频背景的低秩特性,采用非凸γ范数对秩函数进行逼近,考虑视频背景在变换域上仍然具有稀疏性,引入背景在变换域的稀疏先验。其次,引入运动辅助信息矩阵,使其融入前景的运动信息,表示每个像素属于背景的可能性,提高视频运动目标检测的准确度。然后,采用交替方向乘子法(alternating direction method of multipliers, ADMM)对提出的模型进行求解。最后,将提出的方法应用到视频运动目标检测上进行仿真实验。对实验结果的分析表明,提出的RNMALRSD方法比其他基于LRSD的运动目标检测方法具有更高的检测精度。