结构可靠性优化求解的解耦融合策略

在工程结构的可靠性优化过程中,求解的效率和精度是优化方法的关键。该文提出一种针对解耦优化的融合策略。所提方法在优化迭代解耦所用的失效概率函数为前几次迭代设计点构建的局部失效概率函数的加权融合形式。在对原可靠性优化问题进行解耦后,结合序列近似优化方法进行迭代求解。相比于常规的仅使用当次局部建立的失效概率函数而言,所提融合策略最大限度利用了各次迭代中产生的信息用于优化解耦求解,能够提高失效概率函数的近似精度,从而间接达到减少迭代次数和计算量的目的。最后给出了屋架和十杆结构的可靠性优化算例,验证该文方法的正确性和可行性。国家自然科学基金委员会-中国工程物理研究院NSAF联合基金项目(U1530122);;国家自然科学基金青年科学基金项目(51505398

Research on Remote Sensing Image Fusion Based on IHS Color Space

全色图像与多光谱图像是关于同一目标的不同图像，对于获取地球表面土地资源与环境等方面的信息起着非常重要的作用。全色图像通常具有比多光谱图像更丰富的空间细节信息，而多光谱图像提供图像的光谱信息。遥感图像融合用于将两者进行融合，提取全色图像中多光谱图像缺失的空间细节信息，并将该细节信息融合到多光谱图像中，形成具有更高空间分辨率同时不产生光谱失真的多光谱融合图像。遥感图像融合为遥感数据解译及应用提供更精确的数据。目前有很多遥感图像融合方法，按如何将空间细节信息融合到多光谱图像中，大致可归为三类：基于IHS（Intensity，Hue，Saturation）彩色空间方法、基于统计方法及基于变换域方法等。...Panchromatic and multispectral images are very useful for the acquisition of geospatial information about the Earth surface for the assessment of land resources and environment monitoring. They are different images about the same objects. Panchromatic images usually have a better spatial resolution than the multispectral images of the same sensor, while the multispectral images provide spectral pr...学位：工学硕士院系专业：信息科学与技术学院通信工程系_信号与信息处理学号：2332008115332

Sum-modified-Laplacian-based Multifocus Image Fusion Method in Sharp Frequency Localized Contourlet Transform Domain

为了克服Contourlet 融合在远离支撑区间上出现的混叠成分，抑制融合图像在奇异处产生伪吉布斯现象，提出改进拉普拉斯能量和的尖锐频率局部化Contourlet ( Sharp Frequency Localized Contourlet Transform-SFLCT)域多聚焦图像融合方法。首先，采用SFLCT 而不是原始的Contourlet 对多聚焦图像进行分解。接着，将多聚焦图像空域融合方法中评价图像清晰度的指标引入到SFLCT 变换域，采用拉普拉斯能量来选择变换域系数。然后，逆SFLCT 重构得到融合结果。最后，采用循环平移(Cycle Spinning)来提高SFLCT 的平移不变性，有效抑制融合图像在奇异处产生伪吉布斯现象。实验结果表明：对于多聚焦图像，所提方法比循环平移小波变换互信息提高5.87%, QAB/F 提高2.70%,比循环平移Contourlet 方法互信息提高1.77%,QAB/F 提高1.29%,视觉效果优于典型的空域分块拉普拉斯能量方法和平移不变小波变换方法 ============ Abstract: In order to suppress pseudo-Gibbs phenomena around singularities of fused image and reduce significant amount of aliasing components which are located far away from the desired support when the original contourlet is employed in image fusion, Sum-modified-Laplacian-based multifocus image fusion method in sharp frequency localized contourlet transform (SFLCT) domain is proposed. First, SFLCT, instead of the original contourlet, is utilized as the multiscale transform to decompose the source multifocus images into subbands. Second, typical measurements for multifocus image fusion in spatial domain are introduced into contourlet domain and Sum-modified-Laplacian (SML), evidenced in this paper with the best capability to distinguish SFLCT coefficients is from the clear parts or blurry parts of images, is employed in SFCLT subbands as measurement to select SFLCT transform coefficients. Third, inverse SFLCT is used to reconstruct fused image. Finally, cycle spinning is applied to compensate for the lack of translation invariance property and suppress pseudo-Gibbs phenomena of fused images. Using the proposed fusion method, experimental results demonstrate that mutual information is improved by 5.87% and transferred edge information QAB/F is improved by 2.70% compared with cycle spinning wavelet method, while mutual information is improved by 1.77% and QAB/F is improved by 1.29% compared with cycle spinning contourlet method. Meanwhile the proposed fusion method outperforms block-based spatial SML method and shift-invariant wavelet method in term of visual appearance.国家自然科学基金(No.60472081),航空基础科学基金(No.05F07001

An Image Fusion Algorithm Based on Contourlet Transform

图像融合是一项综合同一场景多源图像信息，得到一幅同一场景图像的技术，在图像理解和计算机视觉领域中有着重要的应用价值。从军事应用为目的的数据融合技术开始，融合技术已广泛用于资源管理、城市规划、气象预报、作物及地质分析等领域。本文从变换方法和融合算法两个方面综合研究了多源图像融合技术，提出了一种基于Contourlet变换的改进PCNN融合算法。该算法从变换域和融合算法两个方面对融合进行改进，通过对比多层PCNN神经元的点火次数，更好地提取源图像特征系数，有效保留图像的纹理细节，大大改善了融合结果。 首先介绍了基于小波分解的图像融合算法，给出了小波分解图像融合的实现方案，并对影响该算法的融合结果...Image fusion，which is an important and useful technique for image analysis and computer vision in recent years, is a technique to combine multiple images of the same scene into a new one. This technique has been widely used not only in military application, but also in industry and agriculture fields, such as resources management，town planning，weather forecast and geological analysis. With studyin...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2005130240

改进拉普拉斯能量和的尖锐频率局部化Contourlet域多聚焦图像融合方法

In order to suppress the pseudo-Gibbs phenomena around singularities of fused images and to reduce significant amounts of aliasing components located far away from desired supports when the original Contourlet is employed in the image fusion,a multifocus image fusion method in Sharp Frequency Localized Contourlet Transform(SFLCT) domain based on a sum-modified-Laplacian is proposed.The SFLCT,instead of the original Contourlet,is utilized as the multiscale transform to decompose the original multifocus images into subbands.Then,typical measurements for the multifocus image fusion in a spatial domain are introduced to the Contourlet domain and Sum-modified-Laplacian(SML),and the criterion to distinguish SFLCT coefficients from the clear parts or from blurry parts of images are employed in SFCLT subbands to select the SFLCT transform coefficients.Finally,the inverse SFLCT is used to reconstruct fused images.Moreover,a cycle spinning method is applied to compensate for the lack of translation invariance property and to suppress the pseudo-Gibbs phenomena of fused images.Using the proposed fusion method,experimental results demonstrate that the mutual information has improved by 5.87% and transferred edge information QAB/F has improved by 2.70% as compared with those of the cycle spinning wavelet method,and has improved by 1.77% and 1.29% as compared with those of the cycle spinning Contourlet method.Meanwhile,the proposed fusion method has advantages of good visual effect over the block-based spatial SML method and shift-invariant wavelet method

The research on multi-source information fusion method in Fire Monitoring System

火灾是威胁人民生命安全和社会发展最为经常、普遍的灾害之一。近年来，室内火灾发生率在全球所发生的火灾中占比约百分之八十以上。国际消防技术委员会对这个现象非常的重视，希望各国的相关部门可以对此采取有效的措施。各国为此都采用了比较有效的方法，也就是利用信息科技技术手段对室内火灾环境进行监测预防，使得火灾得到有效防控。 生活中普遍的火灾监测系统中多采用烟雾传感器监测单一的环境参量，并简单地通过阈值法来判断火灾情况。这难免会因为传感器失灵，自然环境影响等不可抗拒的因素造成系统误报或是漏报的概率变大。为了减少这个现象的发生，我们提出了在搭载μC/OS-II系统的STM32平台监测系统中，结合多源信息融合...Fire is one of the mostly frequently and common disasters,which threat to people’s life safety and social development. In recent years, the incidence of indoor fire is about more than eighty percent in the fire, all over the world. The CTIF pay more attention to this phenomenon, hoping the relevant departments of all over the word can take effective measures to solve it. Because of that, many coun...学位：工程硕士院系专业：信息科学与技术学院_电子与通信工程学号：2312012115288

Skin Detection Technology with Fusion Approach

皮肤检测技术发展迅速,并且能够应用于检测和跟踪人体部位、计算机视觉和可视化等多个领域。然而,皮肤检测的主要困难仍然是不同程度的皮肤色调、光照条件和颜色接近肤色的背景等等。本文研究了一种新奇的基于融合策略下的动态皮肤检测,它是由一个平滑动态二维直方图、高斯混合模型和基于脸部皮肤色调颜色计算的实时动态阈值这三种检测方法融合在一起的。本研究通过人脸检测来强化肤色模型,这是因为人脸是不同色调的皮肤颜色的一个突出特征,尤其是在包含不同种族的多个人脸图像中。定性和定量实验结果表明,该方法由于其较低的计算成本和较高的精确度,比目前先进检测技术更稳定有效。The skin detection technology develops rapidly and is capable for a wide range of applications in many fields, such as detect and track the components of human body, computer vision and visualization.However,the principal obstacles faced by skin detection are still the different degrees of skin tone color, illumination conditions and skin color-like backgrounds.This paper proposes a novel skin dynamic detection based on fusion strategy, which fuses a smoothed 2-D histogram, Gaussian model and an online dynamic threshold based on the calculation of face skin tone color.In this research, we adopt face detector to refine the skin model, because face is a prominent indicator of different characteristics of skin tone color, especially in images that include more than one face with different ethnicity.Qualitatively and quantitatively experimental results show that the proposed method is more robust and effective compared to state-of-the-art methods, owing to its low computational costs and high accuracy

Research of Pixel-level Image Fusion Based on Block Variance Voting

随着多传感器技术在众多领域(如计算机视觉、遥感技术、医学图像、军事侦察)的应用和发展，图像融合已经成为一个重要的研究课题。图像融合通过综合多幅图像的信息，获得对同一场景的更为准确全面的描述，以便进一步对图像进行分析理解和对图像中相关目标的检测、识别和跟踪。 本文以像素级图像融合为主要研究方向，针对图像融合过程中的预处理、融合算法、融合效果评价等几个关键问题进行了较为深入的研究，提出了一些新的思路和实现方法。论文主要包括以下内容： 图像融合发展现状以及其应用领域。图像融合的三个层次，即像素级图像融合，特征级图像融合以及决策级图像融合。分析了图像融合在可见光图像、医学诊断、军事、安检、遥感等的...With the developing of multi-sensor technology, Image fusion has become an important research topic. Image fusion has been used in many areas, such as computer vision, remote sensing, medical imaging and military reconnaissance. By using multiple images, the fusion image has more information and more accurate description of the same scene than single image. And the fusion image is very useful for ...学位：工学硕士院系专业：信息科学与技术学院计算机科学系_计算机应用技术学号：2302008115325

基于视觉跟踪的实时视频人脸识别

目前基于深度学习的人脸识别方法准确率高,但是模型复杂,识别速度慢.为了实现监控视频中人脸的实时识别,提出了一种基于视觉跟踪的实时视频人脸识别(RFRV-VT)方法.首先将监控视频的帧序列分组,每一组中分为人脸识别帧和人脸跟踪帧;然后在人脸识别帧中使用基于深度学习的人脸检测和人脸特征提取方法,在人脸跟踪帧中使用基于核相关滤波(KCF)的视觉跟踪方法以加快识别速度.将该方法应用于数据集YouTube Faces(YTF)上进行测试,实验结果显示该算法在监控视频中具有实时性和较高的识别准确性(99.60%).福建省自然科学基金(2015J01288