Extracting the three-dimensional (3D) information including location and height of a pedestrian is important for vision-based intelligent traffic monitoring systems. This paper tackles the relationship between pixels...Extracting the three-dimensional (3D) information including location and height of a pedestrian is important for vision-based intelligent traffic monitoring systems. This paper tackles the relationship between pixels′ actual size and pixels′ spatial resolution through a new method named pixel-resolution mapping (P-RM). The proposed P-RM method derives the equations for pixels′ spatial resolutions (XY-direction) and object′s height (Z-direction) in the real world, while introducing new tilt angle and mounting height calibration methods that do not require special calibration patterns placed in the real world. Both controlled laboratory and actual world experiments were performed and reported. The tests on 3D mensuration using proposed P-RM method showed overall better than 98.7% accuracy in laboratory environments and better than 96% accuracy in real world pedestrian height estimations. The 3D reconstructed images for measured points were also determined with the proposed P-RM method which shows that the proposed method provides a general algorithm for 3D information extraction.展开更多
电子轰击有源像素传感器(electron bombardment active pixel sensor,EBAPS)的光响应非均匀性是指EBAPS中光电阴极被均匀光源照射时,不同像素输出灰度不一致的现象,尤其是在低光环境下,图像的非均匀性会使细节识别变得困难,影响后续图...电子轰击有源像素传感器(electron bombardment active pixel sensor,EBAPS)的光响应非均匀性是指EBAPS中光电阴极被均匀光源照射时,不同像素输出灰度不一致的现象,尤其是在低光环境下,图像的非均匀性会使细节识别变得困难,影响后续图像处理和分析的准确性。光响应非均匀性主要由光电阴极不同区域对光响应的差异、电子敏感互补金属氧化物半导体不同区域的电子倍增特性差异、各像素间对同一激励的响应差异以及读出电路中传输信道的差异性等因素导致。针对EBAPS的非均匀性问题,提出了一种基于EBAPS光电阴极响应、电子倍增以及像素响应非均匀性协同适配的测试方法。实验结果表明,该方法能够有效评价EBAPS的非均匀性,并且能够对器件的测试筛选和算法校正起到指导作用。展开更多
Digital images are frequently contaminated by impulse noise(IN)during acquisition and transmission.The removal of this noise from images is essential for their further processing.In this paper,a two-staged nonlinear f...Digital images are frequently contaminated by impulse noise(IN)during acquisition and transmission.The removal of this noise from images is essential for their further processing.In this paper,a two-staged nonlinear filtering algorithm is proposed for removing random-valued impulse noise(RVIN)from digital images.Noisy pixels are identified and corrected in two cascaded stages.The statistics of two subsets of nearest neighbors are employed as the criterion for detecting noisy pixels in the first stage,while directional differences are adopted as the detector criterion in the second stage.The respective adaptive median values are taken as the replacement values for noisy pixels in each stage.The performance of the proposed method was compared with that of several existing methods.The experimental results show that the performance of the suggested algorithm is superior to those of the compared methods in terms of noise removal,edge preservation,and processing time.展开更多
文摘Extracting the three-dimensional (3D) information including location and height of a pedestrian is important for vision-based intelligent traffic monitoring systems. This paper tackles the relationship between pixels′ actual size and pixels′ spatial resolution through a new method named pixel-resolution mapping (P-RM). The proposed P-RM method derives the equations for pixels′ spatial resolutions (XY-direction) and object′s height (Z-direction) in the real world, while introducing new tilt angle and mounting height calibration methods that do not require special calibration patterns placed in the real world. Both controlled laboratory and actual world experiments were performed and reported. The tests on 3D mensuration using proposed P-RM method showed overall better than 98.7% accuracy in laboratory environments and better than 96% accuracy in real world pedestrian height estimations. The 3D reconstructed images for measured points were also determined with the proposed P-RM method which shows that the proposed method provides a general algorithm for 3D information extraction.
文摘电子轰击有源像素传感器(electron bombardment active pixel sensor,EBAPS)的光响应非均匀性是指EBAPS中光电阴极被均匀光源照射时,不同像素输出灰度不一致的现象,尤其是在低光环境下,图像的非均匀性会使细节识别变得困难,影响后续图像处理和分析的准确性。光响应非均匀性主要由光电阴极不同区域对光响应的差异、电子敏感互补金属氧化物半导体不同区域的电子倍增特性差异、各像素间对同一激励的响应差异以及读出电路中传输信道的差异性等因素导致。针对EBAPS的非均匀性问题,提出了一种基于EBAPS光电阴极响应、电子倍增以及像素响应非均匀性协同适配的测试方法。实验结果表明,该方法能够有效评价EBAPS的非均匀性,并且能够对器件的测试筛选和算法校正起到指导作用。
基金supported by the Opening Project of Key Laboratory of Astronomical Optics & Technology, Nanjing Institute of Astronomical Optics & Technology, Chinese Academy of Sciences (No. CAS-KLAOTKF201308)partly by the special funding for Young Researcher of Nanjing Institute of Astronomical Optics & Technology,Chinese Academy of Sciences(Y-12)
文摘Digital images are frequently contaminated by impulse noise(IN)during acquisition and transmission.The removal of this noise from images is essential for their further processing.In this paper,a two-staged nonlinear filtering algorithm is proposed for removing random-valued impulse noise(RVIN)from digital images.Noisy pixels are identified and corrected in two cascaded stages.The statistics of two subsets of nearest neighbors are employed as the criterion for detecting noisy pixels in the first stage,while directional differences are adopted as the detector criterion in the second stage.The respective adaptive median values are taken as the replacement values for noisy pixels in each stage.The performance of the proposed method was compared with that of several existing methods.The experimental results show that the performance of the suggested algorithm is superior to those of the compared methods in terms of noise removal,edge preservation,and processing time.