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1.发明授权Method for identifying and positioning building using outline region restraint of mountain 有权使用山区轮廓区域约束来识别和定位建筑物的方法公开(公告)号：US09454692B2
公开(公告)日：2016-09-27
申请号：US14714232
申请日：2015-05-15
Inventor： Tianxu Zhang , Li Zhang , Fan Peng , Heng Yao , Cen Lu , Yayun Zheng , Yaxun Wei , Cong Xiao
CPC classification number: G06K9/00201 , G06K9/00208 , G06K9/0063 , G06K9/00637 , G06K9/00697 , G06K9/3241 , G06K9/40 , G06K9/6222 , G06T7/12 , G06T7/155 , G06T7/73 , G06T2207/10004 , G06T2207/10032 , G06T2207/20036 , G06T2207/30181 , G06T2207/30184 , G06T2207/30212
Abstract: A method for identifying and positioning a building using mountain-based outline region restraint, including steps of: (1) obtaining a real-time image, detecting a mountain-based outline of the real-time image, and extending the mountain-based outline thereby obtaining a mountain-based outline restraint region, (2) conducting morphological enhancement and background suppression on the image in the mountain-based outline restraint region, (3) conducting recursive segmentation in the mountain-based outline restraint region thereby transforming an image obtained in step (2) into a binary image, (4) extracting local regions of interest of a target building in the mountain-based outline restraint region according to the binary image, and (5) directly identifying and positioning the target building in the local regions of interest.
Abstract translation: 一种使用山地轮廓区域约束识别和定位建筑物的方法，包括以下步骤：（1）获得实时图像，检测实时图像的山地轮廓，并延伸山基轮廓 从而获得山基轮廓约束区域，（2）对山体轮廓约束区域中的图像进行形态学增强和背景抑制，（3）在山体轮廓约束区域进行递归分割，从而变换所获得的图像 在步骤（2）中成为二进制图像，（4）根据二值图像提取基于山体轮廓约束区域的目标建筑物的局部区域，并且（5）在目标建筑物中直接识别和定位 感兴趣的地区
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Patent Agency Ranking
公开(公告)号：US09625611B2
公开(公告)日：2017-04-18
申请号：US15114651
申请日：2015-02-10
Inventor： Tianxu Zhang , Cen Lu , Yuehuan Wang , Weidong Yang , Nong Sang , Wenxuan Ma , Longwei Hao
CPC classification number: G01V9/005 , G01C21/005 , G06K9/00 , G06K9/0063 , G06K2009/00644
Abstract: The present invention discloses a method for detecting, recognizing, and positioning a zonal underground target in a mountain land environment by detecting a ridge position in the mountain land environment and carrying out energy correction. The method belongs to the interdisciplinary field of pattern recognition, remote sensing technology and terrain analysis. The zonal underground target can cause energy abnormity when the heat field thereof is different from that of a mountain mass, and the heat island effect of the ridge can also cause the energy of the mountain mass to be abnormal. However, the energy abnormity caused by the heat island effect is essentially different from the energy abnormity caused by the zonal underground target in the aspect of mode. Therefore, the present invention aims to achieve an effect of reducing a false alarm rate of detecting and recognizing a zonal underground target in the mountain land environment by eliminating the influence of the heat body effect generated by the ridge in the terrain on the weak energy abnormity mode presented by the zonal underground target. The present invention comprises steps of acquiring digital elevation information of terrain, performing de-noising pretreatment on the digital elevation information, detecting a ridge line, correcting energy at the ridge position, and detecting the zonal underground target.
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3.发明授权Zonal underground structure detection method based on sun shadow compensation 有权基于太阳影子补偿的区域地下结构检测方法公开(公告)号：US09582885B2
公开(公告)日：2017-02-28
申请号：US15106686
申请日：2015-02-10
Inventor： Tianxu Zhang , Longwei Hao , Wenxuan Ma , Cen Lu , Heng Yao , Yuehuan Wang , Nong Sang , Weidong Yang
CPC classification number: G06T7/73 , G01V9/005 , G06K9/0063 , G06K9/4652 , G06K9/4661 , G06T5/008 , G06T5/30 , G06T7/60 , G06T2207/10032 , G06T2207/10048
Abstract: A zonal underground structure detection method based on sun shadow compensation is provided, which belongs to the crossing field of remote sensing technology, physical geography and pattern recognition, and is used to carry out compensation processing after a shadow is detected, to improve the identification rate of zonal underground structure detection and reduce the false alarm rate. The present invention comprises steps of acquiring DEM terrain data of a designated area, acquiring an image shadow position by using DEM, a solar altitude angle and a solar azimuth angle, processing and compensating a shadow area, and detecting a zonal underground structure after the shadow area is corrected. In the present invention, the acquired DEM terrain data is used to detect the shadow in the designated area; and the detected shadow area is processed and compensated, to reduce influence of the shadow area on zonal underground structure detection; finally, the zonal underground structure is detected by using a remote sensing image after shadow compensation, so that the accuracy of zonal underground structure detection is improved and the false alarm rate is reduced compared with zonal underground structure detection using a remote sensing image without shadow compensation processing.
Abstract translation: 提供了一种基于太阳影子补偿的区域性地下结构检测方法，属于遥感技术交叉领域，物理地理和模式识别，用于在检测到阴影后进行补偿处理，提高识别率 区域地下结构检测，降低误报率。 本发明包括以下步骤：获取指定区域的DEM地形数据，通过使用DEM，太阳高度角和太阳方位角获取图像阴影位置，处理和补偿阴影区域，以及在阴影之后检测区域地下结构 区域被更正。 在本发明中，获取的DEM地形数据用于检测指定区域中的阴影; 并对被检测的阴影区域进行处理和补偿，以减少阴影区域对区域地下结构检测的影响; 最后，通过在阴影补偿后使用遥感图像来检测区域性地下结构，从而提高了区域地下结构检测的准确性，并且与使用无影像补偿的遥感图像的区域性地下结构检测相比，误报率降低 处理。
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公开(公告)号：US10365399B2
公开(公告)日：2019-07-30
申请号：US15106703
申请日：2014-09-02
Inventor： Tianxu Zhang , Wenxuan Ma , Cen Lu , Longwei Hao , Yuehuan Wang , Nong Sang , Weidong Yang , Hu Zhu
Abstract: The present invention provides a method for infrared imaging detection and positioning of an underground tubular facility in a plane terrain. Demodulation processing is performed on an original infrared image formed after stratum modulation is generated on the underground tubular facility according to an energy diffusion Gaussian model of the underground tubular facility, so as to obtain a target image of the underground tubular facility. The method comprises: obtaining an original infrared image g formed after stratum modulation is generated on an underground tubular facility; setting an initial value h0 of a Gaussian thermal diffusion function according to the original infrared image g; using the original infrared image g as an initial target image f0, and performing, according to the initial value h0 of the Gaussian thermal diffusion function, iteration solution of a thermal diffusion function hn and a target image fn by by using a single-frame image blind deconvolution method based on a Bayesian theory; and determining whether an iteration termination condition is met, and if the iteration termination condition is met, determining that the target image fn obtained by means of iteration solution this time is a final target image f; and if the iteration termination condition is not met, continuing the iteration calculation. By means of the method, the display of the infrared image of the original underground tubular facility is clearer, and the real structure of the underground tubular facility can also be inverted.
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公开(公告)号：US09741120B2
公开(公告)日：2017-08-22
申请号：US15105456
申请日：2014-09-02
Inventor： Tianxu Zhang , Longwei Hao , Cen Lu , Wenxuan Ma , Yuehuan Wang , Nong Sang , Weidong Yang
CPC classification number: G06T7/70 , G01J5/10 , G01J2005/0077 , G06T5/001 , G06T2207/10048 , G06T2207/20076
Abstract: An infrared imaging detection and positioning method for an underground building in a planar land surface environment comprises: obtaining an original infrared image g0 formed after stratum modulation is performed on an underground building, and determining a local infrared image g of a general position of the underground building in the original infrared image g0; setting an iteration termination condition, and setting an initial value h0 of a Gaussian thermal diffusion function; using the local infrared image g as an initial target image f0, and performing iteration solution of a thermal expansion function hn and a target image fn by using a maximum likelihood estimation algorithm according to the initial value h0 of the Gaussian thermal diffusion function; and determining whether the iteration termination condition is met, if the iteration termination condition is met, using the target image fn obtained by means of iteration solution this time as a final target image f; and if the iteration termination condition is not met, continuing to perform iteration calculation. In the method, by performing demodulation processing on the infrared image formed after stratum modulation is performed on the underground building, the display of the infrared image of the original underground building is clearer, and the real structure of the underground building can be inverted.
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公开(公告)号：US09582862B2
公开(公告)日：2017-02-28
申请号：US15022872
申请日：2015-02-10
Inventor： Tianxu Zhang , Gang Zhou , Ao Zhong , Liangliang Wang , Ming Li , Cen Lu , Wen Zhang , Zhiyong Zuo
IPC: G06T5/00
CPC classification number: G06T5/003 , G06T5/00 , G06T2207/20004 , G06T2207/20012 , G06T2207/20056
Abstract: The invention discloses a direction-adaptive image deblurring method, comprising steps of: (1) defining a minimum cost function for deblurring an image by direction-adaptive total variation regularization; (2) converting the unconstrained minimization problem in step (1) to a constrained problem by auxiliary variables d1=Hu, d2=∇xu and d3=∇yu; (3) obtaining a new minimum cost function from the constrained problem in step (2) by introducing penalty terms; and (4) converting the minimization problem in step (3) to an alternating minimization problem about u, d1, d2 and d3, where a minimum of a variable is calculated as other variables are determined, and obtaining a deblurred image by solving the alternating minimization problem by an alternative and iterative minimization process. Compared with the prior art, the present invention obtains a new direction-adaptive cost function by introducing local direction information into a maximum a posteriori algorithm, solves a problem of edges of an image restored by traditional TV regularization terms being blurred, and can restore images of complex blurring types or images with abundant textures.
Abstract translation: 本发明公开了一种方向自适应图像去模糊方法，包括以下步骤：（1）通过方向自适应总变异规则化定义去除图像的最小成本函数; （2）通过辅助变量d1 = Hu，d2 =∇xu和d3 =∇yu将步骤（1）中的无约束最小化问题转换为约束问题; （3）通过引入惩罚条件，在步骤（2）从约束问题中获得新的最小成本函数; 和（4）将步骤（3）中的最小化问题转换为关于u，d1，d2和d3的交替最小化问题，其中确定变量的最小值作为其他变量，并且通过求解交替 通过替代和迭代最小化过程的最小化问题。 与现有技术相比，本发明通过将局部方向信息引入到最大后验算法中来获得新的方向自适应成本函数，解决了由传统TV正则化术语被模糊而恢复的图像的边缘的问题，并且可以恢复图像 复杂的模糊类型或具有丰富纹理的图像。
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