A Bayesian approach to vectorization of object boundaries from digital images and to geometrical uncertainty assessment

A new Bayesian approach is presented for extracting 2D object boundaries with measures of uncertainty. The boundaries are described by minimal closed sequences of segments and arcs, called mixed polygons. The sequence is minimal in the sense that it is able to describe all the geometrical properties of the boundary without being redundant. Based on geometrical measures evaluated on the object boundary model, a prior distribution is introduced in order to favor a mixed polygon with good geometrical properties, avoiding short sides, collinearity between segments, and so on. The estimation process is based on a two‐stage procedure that combines reversible‐jump MCMC (RJMCMC) and classic MCMC methods. The RJMCMC method is viewed as a model selection technique, and it is used to estimate the correct number of sides of the mixed polygon. The MCMC algorithm provides a sample of mixed polygons through which to evaluate the mixed polygon that best approximates the object boundary and its geometrical uncertainty. A convergence criterion for the RJMCMC method is provided. Copyright © 2011 John Wiley & Sons, Ltd.     

Single-channel color image encryption using phase retrieve algorithm in fractional Fourier domain

A single-channel color image encryption is proposed based on a phase retrieve algorithm and a two-coupled logistic map. Firstly, a gray scale image is constituted with three channels of the color image, and then permuted by a sequence of chaotic pairs generated by the two-coupled logistic map. Secondly, the permutation image is decomposed into three new components, where each component is encoded into a phase-only function in the fractional Fourier domain with a phase retrieve algorithm that is proposed based on the iterative fractional Fourier transform. Finally, an interim image is formed by the combination of these phase-only functions and encrypted into the final gray scale ciphertext with stationary white noise distribution by using chaotic diffusion, which has camouflage property to some extent. In the process of encryption and decryption, chaotic permutation and diffusion makes the resultant image nonlinear and disorder both in spatial domain and frequency domain, and the proposed phase iterative algorithm has faster convergent speed. Additionally, the encryption scheme enlarges the key space of the cryptosystem. Simulation results and security analysis verify the feasibility and effectiveness of this method.     

Theorie und Optimierung der radiometrischen Absorptionsmethode zur Analyse von Binärsystemen

Die Arbeit behandelt theoretisch das Auflösungsvermögen der Absorptionsmethode zur Analyse von Binārsystemen bei Anwendung von monoenergetischer Gamma- und Rötgenstrahlung. Es wird eine analytische Beziehung für die Funktion Δp abgeleitet, die die kleinstmöglichen Veränderung in der Zusammensetzung des Systems chgarakterisiert und die wir noch mittelts dieser Methode in Abhängigkeit von allen zu berückischtigenden Faktoren bestimmen könne. Aus den Extremwerten der Funktion Δp werden dann die optimalen Werte der Energine, der Schichtdicke, der Strahlungshäufigkeit und die Optimalwerte der restlichen Parameter so bestimmt, daβ das Auflösungsvermögen der Methode maximal ist. Die Theorie wird auf eine Ag-Cu-Legierung angewendet.     

电子稳像技术中的坐标变换及像偏移函数分析

为了进行图像偏移的数字补偿 ,需要分析图像的偏移函数 ,要对定坐标系O0 X0 Y0 Z0 ,CCD摄像机载体坐标系O1X1Y1Z1和像空间坐标系O2 X2 Y2 Z2 进行坐标变换 ,从而得出图像偏移与载体运动速度的关系 ,为数字电子稳像奠定基础。     

Dual-mode registration of dynamic contrast-enhanced ultrasound combining tissue and contrast sequences

This study proposes a new method for automatic, iterative image registration in the context of dynamic contrast-enhanced ultrasound (DCE-US) imaging. By constructing a cost function of image registration using a combination of the tissue and contrast-microbubble responses, this new method, referred to as dual-mode registration, performs alignment based on both tissue and vascular structures. Data from five focal liver lesions (FLLs) were used for the evaluation. Automatic registration based on the dual-mode registration technique and tissue-mode registration obtained using the linear response image sequence alone were compared to manual alignment of the sequence by an expert. Comparison of the maximum distance between the transformations applied by the automatic registration techniques and those from expert manual registration reference showed that the dual-mode registration provided better precision than the tissue-mode registration for all cases. The reduction of maximum distance ranged from 0.25 to 9.3 mm. Dual-mode registration is also significantly better than tissue-mode registration for the five sequences with p  -values lower than 0.03$0.03$. The improved sequence alignment is also demonstrated visually by comparison of images from the sequences and the video playbacks of the motion-corrected sequences. This new registration technique better maintains a selected region of interest (ROI) within a fixed position of the image plane throughout the DCE-US sequence. This should reduce motion-related variability of the echo-power estimations and, thus, contribute to more robust perfusion quantification with DCE-US.     

基于能量分布的红外像点定位分析方法

在红外探测器的应用中,常用统计分析、算例验证等方法研究目标成像精确定位问题。鉴于上述方法难以充分阐释物理意义与揭示普遍规律,提出基于能量分布及成像特征的分析方法,针对红外探测目标成像精确定位问题,利用能量分布和数字图像中成像规律,研究像点定位及精度分析。研究了红外目标成像和数字图像特点,建立了定位模型和方法流程;分析了定位误差影响因素,实现了定位结果精度评定;最后结合典型应用实例,进行了计算验证。该方法与已有方法相比,分析过程更直观,获取了红外像点定位分析的理论依据,并给出了定位结果的精度水平:通常红外成像应用中,精度优于1/6像元;在成像较大时,精度可达1/10像元以上。该研究结论对红外探测应用中目标准确定位具有重要意义。     

极值温差红外图像的自适应双局部增强算法

针对目前红外焦平面成像系统在观察目标、特别是极值温差目标时,各温度段灰度描述不均匀和细节不够的问题,提出了一种自适应红外图像双局部增强算法。详细介绍了通过空间分布和灰度统计特性两个方向实现对极值温差图像自适应增强的方法,该方法首先从红外图像的空间分布特性出发,将图像切割成多个局部图像,然后再从直方图灰度分布出发,将局部图像的直方图进行聚类分段,并对分段直方图均衡增强,最后对生成的每个局部图像增强结果进行线性插值拼接完成增强算法。通过在红外焦平面系统中实验证明了极值温差自适应的红外图像双局部增强算法的可行性,并获得了很好的效果,成像质量有明显提高。     

鲁棒的车载红外视频电子稳像算法

针对车辆行进中,红外热像仪拍摄的视频序列存在复杂的随机抖动,提出基于BRISK特征点匹配的运动估计算法,计算出高精度全局运动矢量,同时对于特征点匹配时出现误匹配及场景中存在前景运动物体的情况,采用模糊聚类法分离全局运动和局部运动,提高了算法的鲁棒性。提出了基于Kalman粒子滤波算法,有效实现了复杂扫描运动和随机抖动的分离,并利用双线性插值法进行图像补偿。采用快速图像拼接法进行未定义区域处理,实现了图像全景输出。还利用车载红外热像仪实际拍摄的红外视频进行了稳像实验。实验结果表明,视频序列获得了很好的稳像效果,能够满足实际应用要求。     

基于聚类分割和形态学的可见光与SAR图像配准

针对可见光与SAR图像灰度差异大,共有特征提取难的问题,提出了一种基于k-均值聚类分割和形态学处理的轮廓特征配准方法。利用k-均值聚类算法对两类图像进行分割,得到图像分割区域;通过形态学处理,有效减少SAR图像斑点噪声影响,准确提取两类图像的封闭轮廓;采用轮廓不变矩理论,引入矩变量距离均值、方差约束机制和一致性检查的匹配策略,获取最佳匹配对,实现了两类图像的配准。通过实验,三组图像的配准精度分别达到0.3450、0.2163和0.1810,结果表明该法可行且能达到亚像素的配准精度。     

Difference operators,Green's matrix,sampling theory and applications in signal processing

This paper introduces sampling representations for discrete signals arising from self adjoint difference operators with mixed boundary conditions. The theory of linear operators on finite-dimensional inner product spaces is employed to study the second-order difference operators. We give necessary and sufficient conditions that make the operators self adjoint. The equivalence between the difference operator and a Hermitian Green's matrix is established. Sampling theorems are derived for discrete transforms associated with the difference operator. The results are exhibited via illustrative examples, involving sampling representations for the discrete Hartley transform. Families of discrete fractional Fourier-type transforms are introduced with an application to image encryption.