Efficient Legendre moment computation for grey level images

Legendre orthogonal moments have been widely used in the field of image analysis. Because their computation by a direct method is very time expensive, recent efforts have been devoted to the reduction of computational complexity. Nevertheless, the existing algorithms are mainly focused on binary images. We propose here a new fast method for computing the Legendre moments, which is not only suitable for binary images but also for grey level images. We first establish a recurrence formula of one-dimensional (1D) Legendre moments by using the recursive property of Legendre polynomials. As a result, the 1D Legendre moments of order p, L_p=L_p(0), can be expressed as a linear combination of L_p-1(1) and L_p-2(0). Based on this relationship, the 1D Legendre moments L_p(0) can thus be obtained from the arrays of L₁(a) and L₀(a), where a is an integer number less than p. To further decrease the computation complexity, an algorithm, in which no multiplication is required, is used to compute these quantities. The method is then extended to the calculation of the two-dimensional Legendre moments L_pq. We show that the proposed method is more efficient than the direct method.     

Laplace spectra as fingerprints for image recognition

In the area of image retrieval from data bases and for copyright protection of large image collections there is a growing demand for unique but easily computable fingerprints for images. These fingerprints can be used to quickly identify every image within a larger set of possibly similar images. This paper introduces a novel method to automatically obtain such fingerprints from an image. It is based on a reinterpretation of an image as a Riemannian manifold. This representation is feasible for gray value images and color images. We discuss the use of the spectrum of eigenvalues of different variants of the Laplace operator as a fingerprint and show the usability of this approach in several use cases. Contrary to existing works in this area we do not only use the discrete Laplacian, but also with a particular emphasis the underlying continuous operator. This allows better results in comparing the resulting spectra and deeper insights in the problems arising. We show how the well known discrete Laplacian is related to the continuous Laplace-Beltrami operator. Furthermore, we introduce the new concept of solid height functions to overcome some potential limitations of the method.     

闪光X光噪声图象的局部统计滤波

本文介绍一种噪声图象的滤波方法 ,它不需要先验的图象模型 ,而且也不会损伤边界和细小的细节 ,在相加性和相乘性噪声的情况下 ,计算与边界方向有关的子集的局部平均值和方差 ,相应地沿着边界方向的噪声就被去掉 ,同时对边界有一定的增强效果     

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Kirkpatrick于1982年认识到固体粒子退火过程和组合优化问题有相似性，从而提出了模拟退火算法，并从数学上已证明了模拟退火算法可以取得全局最优解。相比之下，传统的最优化法只能求局部最优值。在计算物质平衡方程时，存在很多不确定的参数，给精确计算带来了一定困难。因此，本文引入模拟退火算法求解物质平衡方程。     

大棚温湿度无线实时监控系统的设计

提出了一种基于ZigBee技术的大棚温湿度无线实时监控系统的设计方法。该方法以SOC芯片CC2530和内核为Cortex-M3的STM32F107及温湿度传感器为硬件平台,可实现对大棚内气体和土壤温湿度的实时采集及空间定位功能,同时可将采集到的数据通过ZigBee网络传输到监控中心。     

基于模拟退火算法的旅行商问题的实现

旅行商问题TSP是一类典型的NP完全问题．围绕着这个问题有各种不同的求解方法,已有的算法例如动态规划法、分支限界法、回溯法等,这些精确式方法都是指数级的,根本无法解决目前的实际问题．贪心法是近似方法．无法达到比较满意的近似比。常用的遗传算法也是求解这类问题的常用方法之一。由于该问题的解是一种特殊的序列．所以遗传算法在求解该问题时的性能也并不理想。模拟退火算法具有描述简单、使用灵活、运用广泛、运行效率高和较少受到初始条件约束等优点．是解决旅行商问题的一种很好的算法。     

对偶四元数线阵遥感影像几何定位

提出以对偶四元数为数学工具进行线阵CCD(电荷耦合元件)遥感影像几何定位的全新技术方法。利用对偶四元数建立遥感通用传感器严密成像模型,将光线束的位置和姿态统一用对偶四元数表示,通过传感器扫描光线在空间中的螺旋运动,实现像点到其对应地面点物方坐标的变换,从而克服了成像几何参数(外方位元素)之间的强相关性。按照空间刚体变换线性蒙皮混合理论,可以把刚体变换矩阵分解为平移和旋转两个部分,对平移部分进行线性插值,对旋转部分进行球面插值,从而实现线阵CCD遥感影像外方位元素的解算。按照所建立的成像几何模型,利用某地区Geoeye-1遥感影像进行几何定位实验,实验结果表明新算法获得的几何定位精度优于传统算法,能够解决定位参数之间的相关性问题。