针对目前图像重建方法去噪效果不佳,导致重建后图像分辨率较低的问题,提出基于单层小波变换的视觉传感图像超分辨率重建方法。建立低分辨率和高分辨率两种识别空间,分别计算含有噪声干扰区域、正常区域以及信道噪声参数三者间的欧式距...针对目前图像重建方法去噪效果不佳,导致重建后图像分辨率较低的问题,提出基于单层小波变换的视觉传感图像超分辨率重建方法。建立低分辨率和高分辨率两种识别空间,分别计算含有噪声干扰区域、正常区域以及信道噪声参数三者间的欧式距离。利用二维平滑函数定义单层小波变换,有效去除视觉传感图像中的噪声,根据多尺度特性对图像中处于边缘微值的分辨率进行具体检测。对所有高分辨率点实行编码,再将编码后的图像系数按照分辨率的高低顺序整理为集合,输出图像完成重建。仿真实验证明,所提方法重建后图像清晰度较高,且结构相似性(Structural Similarity Index Measurement, SSIM)与峰值信噪比(Peak Signal to Noise Ratio, PSNR)的值均高于对比方法,最高值分别为0.95 dB与34.57 dB,说明所提方法的重建效果较好。展开更多
在空对地场景下的目标检测领域中,传统的单阶段检测算法由于固定尺寸的输入,在对大分辨率图像检测时效果较差,尤其当图像中存在较多密集小目标时,漏检现象严重。因此,模仿人眼的目标搜索行为,提出了一种密集场景聚焦的双通道耦合目标检...在空对地场景下的目标检测领域中,传统的单阶段检测算法由于固定尺寸的输入,在对大分辨率图像检测时效果较差,尤其当图像中存在较多密集小目标时,漏检现象严重。因此,模仿人眼的目标搜索行为,提出了一种密集场景聚焦的双通道耦合目标检测算法。算法在You Only Look Once V3(Yolo V3)网络的基础上,增加了密集场景检测通道,对图像中的密集区域进行检测,建立场景耦合结构,将密集场景通道的特征信息与目标实例检测通道的信息进行融合,对检测难度较大的密集区域进行变分辨率检测,以提升对密集小目标的检测精度。在自制空对地密集场景数据集下验证,结果表明,该算法对密集小目标的检测有更好的效果,相比于传统的Yolo V3网络,在检测速度下降9.1帧/s的情况下,平均精度上提升了16.4%。展开更多
The study of the charge conjugation and parity(CP)violation of hyperon is the precision frontier for probing possible new CP violation sources beyond the standard model(SM).With the large number of quantum entangled h...The study of the charge conjugation and parity(CP)violation of hyperon is the precision frontier for probing possible new CP violation sources beyond the standard model(SM).With the large number of quantum entangled hyperonantihyperon pairs to be produced at Super Tau-Charm Facility(STCF),the CP asymmetry of hyperon is expected to be tested with a statistical sensitivity of 10−4 or even better.To cope with the statistical precision,the systematic effects from various aspects are critical and need to be studied in detail.In this paper,the sensitivity effects on the CP violation parameters associated with the detector resolution,including those of the position and momentum,are studied and discussed in detail.The results provide valuable guidance for the design of STCF detector.展开更多
A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models ...A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.展开更多
文摘针对目前图像重建方法去噪效果不佳,导致重建后图像分辨率较低的问题,提出基于单层小波变换的视觉传感图像超分辨率重建方法。建立低分辨率和高分辨率两种识别空间,分别计算含有噪声干扰区域、正常区域以及信道噪声参数三者间的欧式距离。利用二维平滑函数定义单层小波变换,有效去除视觉传感图像中的噪声,根据多尺度特性对图像中处于边缘微值的分辨率进行具体检测。对所有高分辨率点实行编码,再将编码后的图像系数按照分辨率的高低顺序整理为集合,输出图像完成重建。仿真实验证明,所提方法重建后图像清晰度较高,且结构相似性(Structural Similarity Index Measurement, SSIM)与峰值信噪比(Peak Signal to Noise Ratio, PSNR)的值均高于对比方法,最高值分别为0.95 dB与34.57 dB,说明所提方法的重建效果较好。
文摘在空对地场景下的目标检测领域中,传统的单阶段检测算法由于固定尺寸的输入,在对大分辨率图像检测时效果较差,尤其当图像中存在较多密集小目标时,漏检现象严重。因此,模仿人眼的目标搜索行为,提出了一种密集场景聚焦的双通道耦合目标检测算法。算法在You Only Look Once V3(Yolo V3)网络的基础上,增加了密集场景检测通道,对图像中的密集区域进行检测,建立场景耦合结构,将密集场景通道的特征信息与目标实例检测通道的信息进行融合,对检测难度较大的密集区域进行变分辨率检测,以提升对密集小目标的检测精度。在自制空对地密集场景数据集下验证,结果表明,该算法对密集小目标的检测有更好的效果,相比于传统的Yolo V3网络,在检测速度下降9.1帧/s的情况下,平均精度上提升了16.4%。
基金supported by the National Key R&D Program of China(2022YFA1602200)the International Partnership Program of the Chinese Academy of Sciences(211134KYSB20200057).
文摘The study of the charge conjugation and parity(CP)violation of hyperon is the precision frontier for probing possible new CP violation sources beyond the standard model(SM).With the large number of quantum entangled hyperonantihyperon pairs to be produced at Super Tau-Charm Facility(STCF),the CP asymmetry of hyperon is expected to be tested with a statistical sensitivity of 10−4 or even better.To cope with the statistical precision,the systematic effects from various aspects are critical and need to be studied in detail.In this paper,the sensitivity effects on the CP violation parameters associated with the detector resolution,including those of the position and momentum,are studied and discussed in detail.The results provide valuable guidance for the design of STCF detector.
基金Project(T201221207)supported by the Fundamental Research Fund for the Central Universities,ChinaProject(2012CB725301)supported by National Basic Research and Development Program,China
文摘A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.
