基于蒙特卡罗特征降维算法的小样本高光谱图像分类

高光谱图像分类是高光谱数据分析的重要研究内容.相关向量机由于不受梅西定理的限制、不需要设置惩罚因子等优势受到广泛关注.由于高光谱数据具有较高的维数,当训练样本较少时,高光谱数据的分类精度受到严重的影响.通常解决这种现象的办法是对原数据进行特征降维处理,然而多数基于filter模型的特征选择算法无法直接给出最优特征选择个数.为此提出利用蒙特卡罗随机实验可以对特征参量进行统计估计的特性,计算高光谱图像的最优降维特征数,并与相关向量机结合,对降维后的数据进行分类.实验结果表明了使用蒙特卡罗算法求解降维波段数的可靠性.相比较原始末降维数据,降维后的高光谱图像分类精度有较大幅度的提高.     

基于HSI彩色模型的图像降维技术

为了实现快速而准确的图像检索,降低图像维数,通过对HSI色彩空间的分析,将RGB颜色模型转换为基于视觉感知的HSI颜色模型,提出了一种利用HSI颜色模型提取图像主色的图像降维算法。仿真结果表明,该算法无需事先指定需要降维的维数,能较好地利用图像的本征维数,达到图像快速降维的目的。     

基于概率PCA模型的压印字符集本征维数确定方法

提出了一种基于概率主成分分析模型(PPCA)的压印字符图像子空间维数的确定方法。首先,建立观测数据的PPCA模型;然后采用仿真数据进行仿真,对影响维数判别的各种因素进行了分析并给出了3种准则的适用范围;最后对压印字符数据集协方差矩阵的特征值曲线得到本征维数的大致区间范围,通过AIC、BIC和CAIC模型选择准则分别进行最优维数确定。实验表明,该方法可以提高算法的鲁棒性,有效地降低算法的运行时间。     

一种新的隐写分析方法:IKLDA

 如何降低高维数据的维数而不损失原有数据的内在信息是机器学习和数据挖掘领域中的热点问题.本文在图嵌入框架的基础上提出一种新的降维分析算法IKLDA(improved kernel Linear discriminant analysis),不仅使得隐藏在图像的信息能被区分出来,而且大大降低了数据的维数,理论分析及实验结果表明IKLDA的降维隐写分析是有效的,比其它传统降维方法效果要好,并且进一步推进了数据挖掘可视化方法在隐写分析的应用.     

红外多光谱图像仿真方法研究

针对光电武器研制过程中多光谱图像获取困难的问题,提出了一种通过三维立体场景生成红外多光谱仿真图像的方法。该方法能够生成三维场景任意角度的红外仿真图像,并形成特定波长范围的数据立方体。在3~5 m 范围内对特定目标进行了仿真实验,以0.005 m 为步长生成了包含401张红外图像的数据立方体。为体现反射光的方向特性,推导了一种基于Phong 模型的BRDF 模型,并应用于对方向性较强的太阳直接辐射的反射在红外波段的计算,并在3~5 m 范围生成了具有方向特性的红外仿真图像立方体。一系列实验数据表明,该仿真方法可快速生成红外多光谱图像数据立方体,而BRDF 模型能够真实地反映反射的方向特性,提高了仿真图像的逼真度。     

基于结构张量特征值的纹理图像分割模型

通过对结构张量的研究和对纹理图像的分析,提出了一种基于结构张量特征值的标量型纹理特征描述,将其和原图像分别嵌入到两相模糊区域竞争模型和CV模型中,给出了一种纹理和灰度相结合的无监督纹理图像分割模型.为获得新模型的全局最优解,采用了Chambolle对偶法加以实现.针对自然和合成纹理图像进行了相关实验,结果表明该模型特征数据维数少,具有较快的收敛速度和更准确的分割效果.     

基于蒙特卡罗特征降维算法的小样本高光谱图像分类

高光谱图像分类是高光谱数据分析的重要研究内容。相关向量机由于不受梅西定理的限制、不需要设置惩罚因子等优势受到广泛关注。由于高光谱数据具有较高的维数, 当训练样本较少时,高光谱数据的分类精度受到严重的影响。通常解决这种现象的办法是对原数据进行特征降维处理,然而多数基于filter模型的特征选择算法无法直接给出最优特征选择个数。为此提出利用蒙特卡罗随机实验可以对特征参量进行统计估计的特性,计算高光谱图像的最优降维特征数,并与相关向量机结合,对降维后的数据进行分类。实验结果表明了使用蒙特卡罗算法求解降维波段数的可靠性。相比较原始未降维数据,降维后的高光谱图像分类精度有较大幅度的提高。     

真实孔径雷达海洋图像的分形特征分析

结合海洋雷达图像的电磁散射机理,采用小波分析方法对真实孔径雷达海洋图像的分形维数和特征进行分析,发现虽然海洋表面波具有分形的特征,但是海洋雷达图像在布拉格散射机制主导的情况下,不具备分形特征.为了准确计算雷达图像的分形维数,还对差分盒计数法、数学形态学方法和小波分析方法三种分形维数的计算方法进行了评估,通过对已知维数的模拟图像进行分形维数的计算,分析了三种方法的优缺点.     

多帧图像编码孔径光谱成像技术

在双色散结构编码孔径光谱成像系统(DD-CASSI)的基础上,提出了利用多帧采样图方法(Multi Frame-DD-CASSI),以提高信息采样率,并提出新的数学模型,实现了对三维数据立方体的光谱维压缩编码,充分利用了光谱维数据的相关性,利用32帧采样图恢复数据,达到了0.99的光谱曲线相似度和40 db的图像峰值信噪比.     

一种红外图像的形态学分形维数估计算法

分形模型是一种适合于描述具有复杂和不规则形状研究对象的数学模型.自从Mandelbrot将抽象的分形概念和现实世界中的许多自然现象联系起来以后,分形的概念和理论已在相当多的科学研究领域得到了应用.本文在形态学领域研究了分形维数的估计方法.根据分形维数估计方法与形态学梯度的关系,研究了形态学分形维数估计的数学模型,进而提出了一种红外图像分形特征的估计算法.与传统的估计算法相比,该算法准确性高,运算速度快,为实时图像分析提供了一种有效的方法.     

Geometry-assisted image-based rendering for facial analysis and synthesis

In this paper, we present an image-based method for the tracking and rendering of faces. We use the algorithm in an immersive video conferencing system where multiple participants are placed in a common virtual room. This requires viewpoint modification of dynamic objects. Since hair and uncovered areas are difficult to model by pure 3-D geometry-based warping, we add image-based rendering techniques to the system. By interpolating novel views from a 3-D image volume, natural looking results can be achieved. The image-based component is embedded into a geometry-based approach in order to limit the number of images that have to be stored initially for interpolation. Also temporally changing facial features are warped using the approximate geometry information. Both geometry and image cube data are jointly exploited in facial expression analysis and synthesis.     

p XCube云模型的任务划分技术

Query efficiency is bottleneck of XML data cube aggregate query. p XCube is a kind of XML data cube model based on path calculation. Join operations are avoided in this model, but the query efficiency of fact cell is become a new bottleneck. This paper focuses on parallel technology of cloud computing to improve query efficiency of p XCube. Mixed partitioning strategy for fact and dimensions is applied in p XCube cloud model, and the same partitioned vector is adopted. Query parallel algorithm of p XCube cloud model is presented as well. Experiments show that the query cost of p XCube cloud model decreases with the increasing number of parallel nodes gradually. The query cost of fact fragments of each node are close to or even lower than join operations of dimensions , and the Speedup is with better linear. So the model is well suited for decision supported query.     

On the use of radiance domain for burn scar detection under varying atmospheric illumination conditions and viewing geometry

Assessment of damages due to fire, drought, flood, land slide, etc., using hyperspectral images from Hyperion, AVIRIS or HyspIRI has challenging issues. The effects of different illumination, atmospheric conditions and varying sensor/target viewing geometries are some of these challenges. A common approach for target detection is to apply atmospheric correction algorithms to the radiance image data cube and then search within the atmospherically corrected image cube for the target reflectance signature of interest. One major issue with the above approach is that it is computationally demanding. In this paper, instead of applying atmospheric correction to the raw radiance data, we generate radiance profiles of burn scar for the observed atmospheric and illumination conditions at the time of the hyperspectral image data collection and form a radiance profile library using a nonlinear analytical model for radiative transfer and MODTRAN. The target detection has been performed by a spectral similarity technique which takes into consideration multiple radiance profile variants of the target of interest. The effectiveness of the radiance domain-based target detection approach on reducing the computation time has been demonstrated on burn scar detection using airborne AVIRIS image data.     

On the detection of simple points in higher dimensions using cubical homology.

Simple point detection is an important task for several problems in discrete geometry, such as topology preserving thinning in image processing to compute discrete skeletons. In this paper, the approach to simple point detection is based on techniques from cubical homology, a framework ideally suited for problems in image processing. A (d-dimensional) unitary cube (for a d-dimensional digital image) is associated with every discrete picture element, instead of a point in epsilon(d) (the d-dimensional Euclidean space) as has been done previously. A simple point in this setting then refers to the removal of a unitary cube without changing the topology of the cubical complex induced by the digital image. The main result is a characterization of a simple point p (i.e., simple unitary cube) in terms of the homology groups of the (3d - 1) neighborhood of p for arbitrary, finite dimensions     

Wireless Sensor Network for Multi-channel 3D Data Synchronizing Acquisition System and Visual Simulation Research

A multi-channel three-dimension (3D) data synchronizing acquisition system based on wireless sensor network is proposed and used to collect underground three-dimension data in this paper. The channel number and the sampling rate of the data acquisition are the bottleneck of the seismic exploration. The synchronization precision of the multi-channel data affects the oil seismic exploration efficiency directly. The system adopts distributing collecting, conversion, storage and transfer multi-channel seismic data during specific time. The system can synchronizing gather 1024 channel data, and the collective data can form 3D data cube by corresponding process. The data structure of 3D data cube is analyzed and the 3D simulation model of underground oil reservoir is established. The methods of displaying slice for the 3D simulation model are studied using the technology of computer graphic and image processing, and we accomplish the horizontal slices, vertical slices of underground oil reservoir from multi-direction and multi-angle in this paper. Some typical simulation images for an underground oil reservoir are given by programming the corresponding algorithm and graphic display program using C++.     

多面开孔腔体孔缝耦合效应研究

为研究任意入射角度平面波对多面开孔腔体的孔缝耦合效应,根据矢量分析和矩形波导内场强分布对等效传输线法进行了改进,计算了多面开孔腔体内任意位置的屏蔽效能。将改进等效传输线法计算结果与CST仿真结果、实验测量结果进行比较,验证了改进等效传输线法的正确性,相比数值计算方法,改进等效传输线法所需计算时间和内存更少。采用改进等效传输线法对相同体积不同尺寸的多面开孔腔体的屏蔽效能进行了研究,结果表明:在相同体积下,腔体为正方体时的屏蔽效能和其他尺寸腔体的屏蔽效能基本一致,但是正方形的屏蔽效能极小值点大大减少,从而减少了电子设备受电磁干扰的几率。     

Multidimensional analysis method for NOAA AVHRR images

As a fundamental study of multiple image processing, the authors have developed a new technique for the analysis of multispectral remote sensing data. Though the basis of the authors' algorithm is similar to a histogram analysis, they have proposed a novel way of the representation of multidimensional image data, which facilitates a nonexpert to locate and assign different classes present in the data set. The authors' experimentation was done with NOAA satellite image data. The brightness of the received data from channels of different frequency bands are the different dimensions of the multispectral image. By using this method, the authors could successfully classify NOAA satellite data received from the northern part of Japan, and locate the plane areas as an exercise. The authors have quantitatively compared their result with official data. The authors' result was found to be only 1 percent in deviation with the official data     

Analysis of Multiple Orientations

Estimation of local orientations in multivariate signals is an important problem in image processing and computer vision. This general problem formulation also covers optical flow estimation, which can be regarded as orientation estimation in space-time-volumes. Modelling a signal using only a single orientation, however, is often too restrictive, since occlusions and transparencies occur frequently, thus necessitating the modelling and analysis of multiple orientations. We, therefore, develop a unifying mathematical model for multiple orientations: Beyond describing an arbitrary number of orientations in scalar- and vector-valued image data such as color image sequences, it allows the unified treatment of additively and occludingly superimposed oriented structures as well as of combinations of these. Based on this model, we describe estimation schemes for an arbitrary number of additively or occludingly superimposed orientations in images. We confirm the performance of our framework on both synthetic and real image data.     

Combining strings and necklaces for interactive three-dimensional segmentation of spinal images using an integral deformable spine model

Segmentation of the spine directly from three-dimensional (3-D) image data is desirable to accurately capture its morphological properties. We describe a method that allows true 3-D spinal image segmentation using a deformable integral spine model. The method learns the appearance of vertebrae from multiple continuous features recorded along vertebra boundaries in a given training set of images. Important summarizing statistics are encoded into a necklace model on which landmarks are differentiated on their free dimensions. The landmarks are used within a priority segmentation scheme to reduce the complexity of the segmentation problem. Necklace models are coupled by string models. The string models describe in detail the biological variability in the appearance of spinal curvatures from multiple continuous features recorded in the training set. In the segmentation phase, the necklace and string models are used to interactively detect vertebral structures in new image data via elastic deformation reminiscent of a marionette with strings allowing for movement between interrelated structures. Strings constrain the deformation of the spine model within feasible solutions. The driving application in this work is analysis of computed tomography scans of the human lumbar spine. An illustration of the segmentation process shows that the method is promising for segmentation of the spine and for assessment of its morphological properties.     

3-D Kalman filter for image motion estimation

This paper presents a new three-dimensional (3-D) Markov model for motion vector fields. The three dimensions consist of the two space dimensions plus a scale dimension. We use a compound signal model to handle motion discontinuity in this 3-D Markov random field (MRF). For motion estimation, we use an extended Kalman filter as a pel-recursive estimator. Since a single observation can be sensitive to local image characteristics, especially when the model is not accurate, we employ windowed multiple observations at each pixel to increase accuracy. These multiple observations employ different weighting values for each observation, since the uncertainty in each observation is different. Finally, we compare this 3-D model with earlier proposed one-dimensional (1-D) (coarse-to-fine scale) and two-dimensional (2D) spatial compound models, in terms of motion estimation performance on a synthetic and a real image sequence.