基于方向-频率分解的旋转不变性纹理分类

提出了一种用于纹理分类的旋转不变性特征提取的新算法.该算法是将一定大小的图像进行二维傅里叶变换;其次在变换后的图像中央选择一个圆盘区域,并在方向[0°,180°]内进行等间隔角度频率抽样,实现方向分解,使用一组复Morlet小波对每个方向上的映射切片进行小波变换,从而实现多通道频率分解;在各个频率通道中计算均值和方差作为特征,并利用线性回归模型计算频率通道之间的关系特征;将特征沿方向进行一维傅里叶变换并取其幅值,从而得到旋转不变性特征.实验结果表明所提取的特征具有较好的旋转不变性,与其它算法相比具有更好的分类性能,并且对无旋转纹理分类也能产生较好的分类结果.     

离焦模糊图像中汉字识别技术研究

提出了辐射投影变换(RPT),给出了数学模型和实现方法以及相应的投影函数(RPTF)。为了进一步提高其性能,对原始投影变换进行了优化改进,即累加原始函数的值并作旋转变换,从而得到了改进投影累加函数(IPAF),它可直接用于离焦模糊图像中汉字的识别。将傅里叶变换应用到IPAF上,使描述和识别用的特征量大为减少。采用基于IPAF的傅里叶子(前8个傅里叶系数)作为特征量,对离焦模糊的一级汉字进行识别,总识别率达到了97 4%。     

基于科赫曲线分形结构太赫兹带通滤波器

太赫兹滤波器是太赫兹通信、太赫兹成像和太赫兹检测等太赫兹应用系统中不可或缺的功能器件。按照不同的分类方式,滤波器有不同的种类,常见的按照选频功能可分为高通滤波器、低通滤波器、带阻滤波器和带通滤波器。为了实现在太赫兹波段的滤波效果,世界各地的研究人员利用不同的结构、材料和控制方式实现了功能各异的太赫兹滤波器,但是考虑到设计的器件要应用到太赫兹系统中,成本低廉、结构简单、性能优越的太赫兹滤波器一直是研究人员的追求。分形概念自提出以来在很多研究领域都有了快速发展,但是在太赫兹波段的应用还不是很常见,特别是应用于太赫兹功能器件的设计。引入分形中科赫曲线的概念设计并制备了一种新型的太赫兹带通滤波器,该滤波器是在金属薄膜上刻蚀出科赫曲线分形结构,当太赫兹波垂直入射到该滤波器时候实现了在太赫兹波段的窄带滤波。在滤波器的设计过程中,追求理论与实验相结合,首先在电磁仿真软件中建立科赫曲线分形结构滤波器模型进行计算,探究分形结构应用于太赫兹波段进行滤波的可行性,在进行多次计算之后得到优化后的尺寸和结构,然后根据优化后的尺寸加工出科赫曲线分形结构太赫兹滤波器样品,并且将样品放在太赫兹时域光谱系统中进行实验测量,得到实验数据后与仿真结果进行比较。在仿真中利用了时域有限差分法模拟科赫曲线分形结构太赫兹带通滤波器的传输特性,优化后的仿真结果表明:滤波器的谐振频率为0.715 THz,透射系数能够达到0.92,-3 dB带宽为21.9 GHz,将仿真得到的散射参数进行S参数反演得到了太赫兹滤波器样品的电磁参数,这在理论上分析了太赫兹波在谐振点处产生透射增强的原因。利用飞秒激光微加工系统制备了尺寸优化后的科赫曲线分形结构太赫兹带通滤波器样品,然后使用太赫兹时域光谱系统对样品的传输特性进行测试,对实验得到的时域数据进行快速傅里叶变换之后得到频域数据,再把频域数据进行归一化处理后与之前的电磁仿真结果进行对比,发现实验测得的结果与电磁软件仿真得到的结果较为吻合。     

一种抗噪分形维计算方法及其在声纳图像识别中的应用

用于计算图像分形维的差分盒计数法(DBC)和鲁棒差分盒计数法(RDBC)都对脉冲噪声和斑点噪声较敏感,为此本文提出一种抗噪差分盒计数法(NRDBC),利用剪切局部标准差(TLSD)来计算图像分形维,由于TLSD可有效滤除脉冲噪声和斑点噪声、且对高斯噪声敏感性小,因此NRDBC能对有噪图像进行可靠的分形维估计。利用多分辨率的DBC、RDBC和NRDBC对混有高斯噪声、脉冲噪声和斑点噪声的7种Brodatz纹理以及3种海底的侧扫声纳图像进行了分类实验,结果表明,本文提出的NRDBC可获得更高的识别率和更好的抗噪性。     

基于分维特征和反向传播神经网络的自然纹理识别

提出一种利用分维特征, 即自然纹理的自相似性进行纹理识别的研究。利用原始图像、高灰度图像、低灰度图像、四个方向（０°, ４５°, ９０°, １３５°）的梯度图像及二阶多分维共八个分维数作为特征值; 分维的计算采用改进的盒子计数法（ＭＢＣＭ）; 最后利用反向传播（ＢＰ）神经网络进行纹理的分类识别。实验结果与其它技术进行了比较, 并提出利用维纳滤波进一步改进分类性能。     

Multiscale top-hat selection transform based infrared and visual image fusion with emphasis on extracting regions of interest

To effectively combine regions of interest in original infrared and visual images, an adaptively weighted infrared and visual image fusion algorithm is developed based on the multiscale top-hat selection transform. First, the multiscale top-hat selection transform using multiscale structuring elements with increasing sizes is discussed. Second, the image regions of the original infrared and visual images at each scale are extracted by using the multiscale top-hat selection transform. Third, the final fusion regions are constructed from the extracted multiscale image regions. Finally, the final fusion regions are combined into a base image calculated from the original images to form the final fusion result. The combination of the final fusion regions uses the adaptive weight strategy, and the weights are adaptively obtained based on the importance of the extracted features. In the paper, we compare seven image fusion methods: wavelet pyramid algorithm (WP), shift invariant discrete wavelet transform algorithm (SIDWT), Laplacian pyramid algorithm (LP), morphological pyramid algorithm (MP), multiscale morphology based algorithm (MSM), center-surround top-hat transform based algorithm (CSTHT), and the proposed multiscale top-hat selection transform based algorithm. These seven methods are compared over five different publicly available image sets using three metrics of spatial frequency, mean gradient, and Q. The results show that the proposed algorithm is effective and may be useful for the applications related to the infrared and visual image fusion.     

Implementing compressive fractional Fourier transformation with iterative kernel steering regression in double random phase encoding

This paper proposes a novel approach in double random phase encryption based on compressive fractional Fourier transform along with the kernel steering regression. The method increases the complexity of the image by using fractional Fourier transform and taking fewer measurements from the image data. Numerical results are given to analyze the validity of this technique. Considering natural images to be sparse in some domain, we apply a compressive sensing (CS) approach by using a TwIST algorithm. The encryption process has kernel steering regression algorithm for denoising and compressive sensing technique for image compression along with the fractional Fourier transform that makes the image in more complex form.     

基于区域分维和非采样Contourlet变换的图像融合算法

针对源图像有用信息的提取,提出了基于区域分维和非下采样Contourlet变换相结合的红外与可见光图像融合算法.将图像的区域属性、区域大小、边缘强度以及纹理显著程度等特点用图像不同尺度上的区域分维进行描述,对于非下采样Contourlet变换低频系数,根据源图像不同尺度上的区域分维进行基于系数选择的融合.针对带通子带系数设计了系数局部匹配度算子,依据匹配度不同采用加权和系数选取相结合的融合规则.与其他常规融合方法进行比较,该算法可有效实现红外与可见光图像的融合.     

具有任意方向的扇形滤波器及其在图像方向检测中的应用

扇形滤波器在图像的方向检测中是非常重要的.本文基于极傅里叶变换和一个楔形滤波器,设计出具有任意方向的二维扇形滤波器.首先,楔形滤波器被变换到极傅里叶域,再利用极傅里叶变换的旋转特性,楔形滤波器可以通过将其极傅里叶变换沿着水平方向进行移动来实现旋转,得到一系列具有任意方向导向的扇形滤波器,它们能够检测图像中所包含的任意方向信息.由于整个设计过程不涉及二维优化,因此所提出的设计方法具有设计简单的优点.为了验证扇形滤波器的方向敏感性,将所设计的扇形滤波器应用于图像的纹理方向检测,结果表明,具有任意方向的扇形滤波器在图像纹理方向检测中具有很大的潜能.     

Multifocus image fusion scheme using focused region detection and multiresolution

To solve the fusion problem of the multifocus images of the same scene, a novel algorithm based on focused region detection and multiresolution is proposed. In order to integrate the advantages of spatial domain-based fusion methods and transformed domain-based fusion methods, we use a technique of focused region detection and a new fusion method of multiscale transform (MST) to guide pixel combination. Firstly, the initial fused image is acquired with a novel multiresolution image fusion method. The pixels of the original images, which are similar to the corresponding initial fused image pixels, are considered to be located in the sharply focused regions. By this method, the initial focused regions can be determined, and the techniques of morphological opening and closing are employed for post-processing. Then the pixels within the focused regions in each source image are selected as the pixels of the fused image; meanwhile, the initial fused image pixels which are located at the focused border regions are retained as the pixels of the final fused image. The fused image is then obtained. The experimental results show that the proposed fusion approach is effective and performs better in fusing multi-focus images than some current methods.     

Affine invariant feature extraction algorithm based on multiscale autoconvolution combining with texture structure analysis

Affine invariant feature extraction has been one of the key issues for object recognition, especially for the images captured under the variable environments. Considering that multiscale autoconvolution feature (MSA), which has the prominent comprehensive performance, is very sensitive to illumination change, a novel algorithm of extracting affine invariant feature is proposed based on the MSA transform combining with texture structure analysis. Firstly, a new MSA feature is extracted from texture structure map of the image which is computed based on local binary pattern theory. And then the original image based MSA and the texture map based MSA are combined to a new feature using generalized canonical correlation analysis, called TFMSA. This new feature represents much more image information than the traditional one and is performed in various object recognition tasks. The experimental results indicate that the new TFMSA not only conquers the defect of the traditional MSA, but also has good adaptability for a certain range of viewing angles, partial occlusion, uniform and non-uniform illumination changes. The recognition accuracy of the new feature is superior to MSA and other improved methods.     

Fractality of self-grown nanostructured tungsten by He plasma irradiation

Fractal property of the helium irradiated nanostructured tungsten was investigated from the scanning electron microscope (SEM) micrographs, gas adsorption isotherms, and transmission electron microscope (TEM) micrographs. From the SEM micrographs, fractal dimension and the parameter _dmin$d_{\min }$, which characterizes the SEM texture image, were deduced, and the fractal dimension was compared with the one obtained from the gas adsorption isotherms. It was revealed that the fractal dimension obtained from the top view SEM micrographs was significantly lower than that from the adsorption isotherms. From the cross sectional SEM micrographs, two power law relations were identified in two different scales, and the fractal dimension from the adsorption was in between the two fractal dimensions. From the TEM micrographs, it was found that the porosity distribution also has fractal relation with height of the nanostructures when the nanostructures were sufficiently grown.     

基于分形脊波神经网络的遥感图像分类研究

在分形理论和脊波神经网络的基础上，综合利用彩色遥感图像的光谱、纹理和形状特征，提出了一种彩色遥感图像的分类新方法．该方法把彩色图像的蓝、绿、红波段作为3个光谱特征，由分形理论计算的DBC维和多重分形维数作为2个纹理特征，平均不变矩作为1个形状特征，并利用对曲线具有极强方向识别能力的脊波神经网络作为分类器．实验结果表明，提出的彩色遥感图像分类方法具有较高的分类准确率和较强的抗噪音能力．     

基于Contourlet变换与FLD的人脸表情识别方法

提出了一种基于Contourlet变换与FLD的人脸表情特征提取方法。Contourlet变换是一种新的多尺度几何分析方法,它在具备小波变换的多分辨率特性和时频局部特性的同时,还具有很强的多方向选择性和各向异性。图像经过Contourlet变换后的低频分量可体现表情的概貌,高频方向子带可体现表情的轮廓和纹理等细节。将低频分量与部分高频方向子带结合起来作为整体特征,可压缩图像的数据量,并能够体现表情的本质特征。首先用Fisher线性判别法(FLD)进行特征提取,然后采用K-近邻法进行分类。实验证明,该方法比经典的FLD方法有着更快的特征提取速度和更高的表情识别率。     

Experimental determination of Hurst exponent of the self-affine fractal patterns with optical fractional Fourier transform

The extension of ordinary Fourier transform to the fractional Fourier transform (FRFT) was first accomplished by Namias in 1980. He gave a complete mathematical definition and discussed the eigenfunction of the transform. Using a system of lenses Lohmann et al.[1] first successfully realized the FRFT optically and designed the single lens mode and double lens mode for the realization of the FRFT of continuously variable fractional order. The concept of fractals was first proposed by Man…