In this paper, the problem of locally optimum detection of weak pulse signals in narrow-band non-Gaussian noise is discussed. A generalized model is proposed for locally optimum detectors (LOD) and the corresponding p...In this paper, the problem of locally optimum detection of weak pulse signals in narrow-band non-Gaussian noise is discussed. A generalized model is proposed for locally optimum detectors (LOD) and the corresponding physical meaning is explained. On the basis of this generalized model, the LOD structures are derived for detecting both coherent- and incoherent-pulse signals in narrow-band non-Gaussian noise. The asymptotic relative efficiency (ARE) due to Pitman is used to evaluate the performance of these LODs. Finally, numerical calculations are carried out for the AREs of these LODs and some valuable results are obtained.展开更多
For vision-based mobile robot navigation, images of the same scene may undergo a general affine transformation in the case of significant viewpoint changes. So, a novel method for detecting affine invariant interest p...For vision-based mobile robot navigation, images of the same scene may undergo a general affine transformation in the case of significant viewpoint changes. So, a novel method for detecting affine invariant interest points is proposed to obtain the invariant local features, which is coined polynomial local orientation tensor(PLOT). The new detector is based on image local orientation tensor that is constructed from the polynomial expansion of image signal. Firstly, the properties of local orientation tensor of PLOT are analyzed, and a suitable tuning parameter of local orientation tensor is chosen so as to extract invariant features. The initial interest points are detected by local maxima search for the smaller eigenvalues of the orientation tensor. Then, an iterative procedure is used to allow the initial interest points to converge to affine invariant interest points and regions. The performances of this detector are evaluated on the repeatability criteria and recall versus 1-precision graphs, and then are compared with other existing approaches. Experimental results for PLOT show strong performance under affine transformation in the real-world conditions.展开更多
Antenna-coupled field-effect-transistors(FETs) offer high sensitivity for terahertz detection. Both the magnitude and the polarity of the response signal are sensitive to the localized terahertz field under the gate. ...Antenna-coupled field-effect-transistors(FETs) offer high sensitivity for terahertz detection. Both the magnitude and the polarity of the response signal are sensitive to the localized terahertz field under the gate. The ability of accurate sensing the intensity pattern is required for terahertz imaging systems. Here, we report artefacts in the intensity pattern of a focused terahertz beam around 1 THz by scanning a silicon-lens and antenna coupled AlGaN/GaN high-electron-mobility-transistor(HEMT) detector. The origin of the image distortion is found to be connected with one of the antenna blocks by probing the localized photocurrents as a function of the beam location and the frequency. Although the exact distortion is found with our specific antenna design, we believe similar artefacts could be commonplace in antenna-coupled FET terahertz detectors when the beam spot becomes comparable with the antenna size. To eliminate such artefacts, new antenna designs are welcomed to achieve strong asymmetry in the terahertz field distribution under the gate while maintaining a more symmetric radiation pattern for the whole antenna.展开更多
相比基于特征点的传统图像特征匹配算法,基于深度学习的特征匹配算法能产生更大规模和更高质量的匹配.为获取较大范围且清晰的路面裂缝图像,并解决弱纹理图像拼接过程中发生的匹配对缺失问题,本文基于深度学习LoFTR(detector-free local...相比基于特征点的传统图像特征匹配算法,基于深度学习的特征匹配算法能产生更大规模和更高质量的匹配.为获取较大范围且清晰的路面裂缝图像,并解决弱纹理图像拼接过程中发生的匹配对缺失问题,本文基于深度学习LoFTR(detector-free local feature matching with Transformers)算法实现路面图像的拼接,并结合路面图像的特点,提出局部拼接方法缩短算法运行的时间.先对相邻图像做分割处理,再通过LoFTR算法产生密集特征匹配,根据匹配结果计算出单应矩阵值并实现像素转换,然后通过基于小波变换的图像融合算法获得局部拼接后的图像,最后添加未输入匹配网络的部分图像,得到相邻图像的完整拼接结果.实验结果表明,与基于SIFT(scale-invariant feature transform)、SURF(speeded up robust features)、ORB(oriented FAST and rotated BRIEF)的图像拼接方法比较,研究所提出的拼接方法对路面图像的拼接效果更佳,特征匹配阶段产生的匹配结果置信度更高.对于两幅路面图像的拼接,采用局部拼接方法耗费的时间较改进之前缩短了27.53%.研究提出的拼接方案是高效且准确的,能够为道路病害监测提供总体病害信息.展开更多
文摘In this paper, the problem of locally optimum detection of weak pulse signals in narrow-band non-Gaussian noise is discussed. A generalized model is proposed for locally optimum detectors (LOD) and the corresponding physical meaning is explained. On the basis of this generalized model, the LOD structures are derived for detecting both coherent- and incoherent-pulse signals in narrow-band non-Gaussian noise. The asymptotic relative efficiency (ARE) due to Pitman is used to evaluate the performance of these LODs. Finally, numerical calculations are carried out for the AREs of these LODs and some valuable results are obtained.
基金Projects(61203332,61203208) supported by the National Natural Science Foundation of China
文摘For vision-based mobile robot navigation, images of the same scene may undergo a general affine transformation in the case of significant viewpoint changes. So, a novel method for detecting affine invariant interest points is proposed to obtain the invariant local features, which is coined polynomial local orientation tensor(PLOT). The new detector is based on image local orientation tensor that is constructed from the polynomial expansion of image signal. Firstly, the properties of local orientation tensor of PLOT are analyzed, and a suitable tuning parameter of local orientation tensor is chosen so as to extract invariant features. The initial interest points are detected by local maxima search for the smaller eigenvalues of the orientation tensor. Then, an iterative procedure is used to allow the initial interest points to converge to affine invariant interest points and regions. The performances of this detector are evaluated on the repeatability criteria and recall versus 1-precision graphs, and then are compared with other existing approaches. Experimental results for PLOT show strong performance under affine transformation in the real-world conditions.
基金Project supported by the National Key Research and Development Program of China(Grant No.2016YFF0100501)the National Natural Science Foundation of China(Grant Nos.61771466,61775231,and 61611530708)+3 种基金the Six Talent Peaks Project of Jiangsu Province,China(Grant No.XXRJ-079)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2017372)the Russian Foundation for Basic Research(Grant No.17-52-53063)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20160400)
文摘Antenna-coupled field-effect-transistors(FETs) offer high sensitivity for terahertz detection. Both the magnitude and the polarity of the response signal are sensitive to the localized terahertz field under the gate. The ability of accurate sensing the intensity pattern is required for terahertz imaging systems. Here, we report artefacts in the intensity pattern of a focused terahertz beam around 1 THz by scanning a silicon-lens and antenna coupled AlGaN/GaN high-electron-mobility-transistor(HEMT) detector. The origin of the image distortion is found to be connected with one of the antenna blocks by probing the localized photocurrents as a function of the beam location and the frequency. Although the exact distortion is found with our specific antenna design, we believe similar artefacts could be commonplace in antenna-coupled FET terahertz detectors when the beam spot becomes comparable with the antenna size. To eliminate such artefacts, new antenna designs are welcomed to achieve strong asymmetry in the terahertz field distribution under the gate while maintaining a more symmetric radiation pattern for the whole antenna.
文摘相比基于特征点的传统图像特征匹配算法,基于深度学习的特征匹配算法能产生更大规模和更高质量的匹配.为获取较大范围且清晰的路面裂缝图像,并解决弱纹理图像拼接过程中发生的匹配对缺失问题,本文基于深度学习LoFTR(detector-free local feature matching with Transformers)算法实现路面图像的拼接,并结合路面图像的特点,提出局部拼接方法缩短算法运行的时间.先对相邻图像做分割处理,再通过LoFTR算法产生密集特征匹配,根据匹配结果计算出单应矩阵值并实现像素转换,然后通过基于小波变换的图像融合算法获得局部拼接后的图像,最后添加未输入匹配网络的部分图像,得到相邻图像的完整拼接结果.实验结果表明,与基于SIFT(scale-invariant feature transform)、SURF(speeded up robust features)、ORB(oriented FAST and rotated BRIEF)的图像拼接方法比较,研究所提出的拼接方法对路面图像的拼接效果更佳,特征匹配阶段产生的匹配结果置信度更高.对于两幅路面图像的拼接,采用局部拼接方法耗费的时间较改进之前缩短了27.53%.研究提出的拼接方案是高效且准确的,能够为道路病害监测提供总体病害信息.
