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1. 发明授权

US06618503B2 Image demosaicing method utilizing directional smoothing 失效
公开(公告)号：US06618503B2
公开(公告)日：2003-09-09
申请号：US10095198
申请日：2002-03-11
申请人： Yacov Hel-or , Daniel Keren
发明人： Yacov Hel-or , Daniel Keren
IPC分类号： G06K900
CPC分类号： G06T3/4015 , H04N9/045
摘要： A method for operating a data processing system to generate a full color image from a partially sampled version of the image. The full color image includes a first two-dimensional array of vectors having components representing the intensity of a pixel in the full color image in a corresponding spectral band at a location determined by the location of the vector in the first two-dimensional array. The method generates the first two-dimensional array from a two-dimensional array of scalars. Each scalar determines one of the first, second, or third intensity values at a corresponding location in the two-dimensional array of vectors. The method determines the remaining ones of the first, second, and third intensity values. The method starts by assigning a value to each one of the components of the vectors in the first two-dimensional array of vectors that is not determined by one of the scalars. A luminance image and first and second chrominance images are then generated from the first two-dimensional array of vectors. The chrominance images are filtered with an isotropic low-pass spatial filter to generate filtered chrominance images. The two-dimensional array of vectors is then regenerated from the luminance image and the first and second filtered chrominance images. The scalars that are originally given by the sensors are reset in the regenerated two-dimensional array of vectors. The decomposition, filtering, resetting, and regenerating steps are iterated to provide the final full-color image. In the preferred embodiment, the luminance image is also filtered. However, the filtering of the luminance image utilizes a low-pass spatial filter having an anisotropy that varies with location in the luminance image.

2. 发明授权

US06404918B1 Image demosaicing method utilizing directional smoothing 失效
标题翻译：使用定向平滑的图像去马赛克方法
公开(公告)号：US06404918B1
公开(公告)日：2002-06-11
申请号：US09303772
申请日：1999-04-30
申请人： Yacov Hel-or , Daniel Keren
发明人： Yacov Hel-or , Daniel Keren
IPC分类号： G06K900
CPC分类号： G06T3/4015 , H04N9/045
摘要： A method for operating a data processing system to generate a full color image from a partially sampled version of the image. The full color image includes a first two-dimensional array of vectors having components representing the intensity of a pixel in the full color image in a corresponding spectral band at a location determined by the location of the vector in the first two-dimensional array. The method generates the first two-dimensional array from a two-dimensional array of scalars. Each scalar determines one of the first, second, or third intensity values at a corresponding location in the two-dimensional array of vectors. The method determines the remaining ones of the first, second, and third intensity values. The method starts by assigning a value to each one of the components of the vectors in the first two-dimensional array of vectors that is not determined by one of the scalars. A luminance image and first and second chrominance images are then generated from the first two-dimensional array of vectors. The chrominance images are filtered with an isotropic low-pass spatial filter to generate filtered chrominance images. The two-dimensional array of vectors is then regenerated from the luminance image and the first and second filtered chrominance images. The scalars that are originally given by the sensors are reset in the regenerated two-dimensional array of vectors. The decomposition, filtering, resetting, and regenerating steps are iterated to provide the final full-color image. In the preferred embodiment, the luminance image is also filtered. However, the filtering of the luminance image utilizes a low-pass spatial filter having an anisotropy that varies with location in the luminance image.
摘要翻译：一种用于操作数据处理系统以从图像的部分采样版本生成全色图像的方法。全色图像包括具有表示在由第一二维阵列中的矢量的位置确定的位置处的相应光谱带中全色图像中的像素的强度的分量的向量的第一二维阵列。该方法从标量的二维数组生成第一个二维数组。每个标量在二维向量阵列中的相应位置处确定第一，第二或第三强度值中的一个。该方法确定第一，第二和第三强度值中的其余值。该方法开始于向量的第一个二维数组中的矢量的每个分量赋值，该数组不是由一个标量决定的。然后从第一二维向量阵列生成亮度图像和第一和第二色度图像。用各向同性低通空间滤波器对色度图像进行滤波，以产生经滤波的色度图像。然后从亮度图像和第一和第二滤波色度图像再生二维向量阵列。最初由传感器给出的标量在再生的二维向量阵列中被复位。迭代分解，滤波，复位和再生步骤以提供最终的全色图像。在优选实施例中，也对亮度图像进行滤波。然而，亮度图像的滤波利用具有随着亮度图像中的位置而变化的各向异性的低通空间滤波器。

3. 发明申请

US20090310496A1 MONITORING THRESHOLD FUNCTIONS OVER DISTRIBUTED DATA SETS 有权
标题翻译：通过分布式数据集监控阈值函数
公开(公告)号：US20090310496A1
公开(公告)日：2009-12-17
申请号：US12293383
申请日：2007-03-14
申请人： Assaf Schuster , Daniel Keren , Izchak Sharfman
发明人： Assaf Schuster , Daniel Keren , Izchak Sharfman
IPC分类号： H04L12/26
CPC分类号： G06F11/3495 , G06F11/3404 , G06F11/3447 , G06F2201/81 , G06F2201/875
摘要： A method for distributed computing includes processing multiple sets of data at respective computing nodes (24), and calculating respective local values of one or more statistical parameters characterizing the sets of the data. A global condition is defined, such that the condition is violated when a function defined over a weighted average of the respective local values crosses a predetermined threshold. The global condition is separated into a plurality of local constraints, which include a respective local constraint to be evaluated by each of the nodes based on the respective local values, such that violation of the respective local constraint in at least one of the nodes indicates a violation of the global condition. The local constraint is evaluated independently at each of the nodes. When at least one of the nodes detects that the respective local constraint is violated, an indication that the global condition has been violated is produced.
摘要翻译：一种用于分布式计算的方法包括：处理各个计算节点（24）处的多组数据，以及计算表征数据集的一个或多个统计参数的各自本地值。定义全局条件，使得当在相应局部值的加权平均值上定义的功能跨越预定阈值时，该条件被违反。全局条件被分成多个局部约束，其包括基于各个本地值由每个节点评估的相应的局部约束，使得至少一个节点上的相应局部约束的违反指示违反全球条件。每个节点独立地评估局部约束。当至少一个节点检测到相应的本地约束被违反时，产生了全局条件已被违反的指示。

4. 发明授权

US08332458B2 Monitoring threshold functions over distributed data sets 有权
标题翻译：在分布式数据集上监视阈值函数
公开(公告)号：US08332458B2
公开(公告)日：2012-12-11
申请号：US12293383
申请日：2007-03-14
申请人： Assaf Schuster , Daniel Keren , Izchak Sharfman
发明人： Assaf Schuster , Daniel Keren , Izchak Sharfman
IPC分类号： G06F15/16
CPC分类号： G06F11/3495 , G06F11/3404 , G06F11/3447 , G06F2201/81 , G06F2201/875
摘要： A method for distributed computing includes processing multiple sets of data at respective computing nodes (24), and calculating respective local values of one or more statistical parameters characterizing the sets of the data. A global condition is defined, such that the condition is violated when a function defined over a weighted average of the respective local values crosses a predetermined threshold. The global condition is separated into a plurality of local constraints, which include a respective local constraint to be evaluated by each of the nodes based on the respective local values, such that violation of the respective local constraint in at least one of the nodes indicates a violation of the global condition. The local constraint is evaluated independently at each of the nodes. When at least one of the nodes detects that the respective local constraint is violated, an indication that the global condition has been violated is produced.
摘要翻译：一种用于分布式计算的方法包括：处理各个计算节点（24）处的多组数据，以及计算表征数据集的一个或多个统计参数的各自本地值。定义全局条件，使得当在相应局部值的加权平均值上定义的功能跨越预定阈值时，该条件被违反。全局条件被分成多个局部约束，其包括基于各个本地值由每个节点评估的相应局部约束，使得至少一个节点中的相应局部约束的违反指示违反全球条件。每个节点独立地评估局部约束。当至少一个节点检测到相应的本地约束被违反时，产生了全局条件已被违反的指示。

5. 发明授权

US08949409B2 Method and system of managing and/or monitoring distributed computing based on geometric constraints 有权
标题翻译：基于几何约束管理和/或监控分布式计算的方法和系统
公开(公告)号：US08949409B2
公开(公告)日：2015-02-03
申请号：US12817242
申请日：2010-06-17
申请人： Assaf Schuster , Daniel Keren , Guy Sagy , Izchak Sherfman
发明人： Assaf Schuster , Daniel Keren , Guy Sagy , Izchak Sherfman
IPC分类号： G06F15/173 , H04L29/08 , G06F11/30
CPC分类号： H04L67/125 , G06F11/3006 , G06F11/3058 , H04L67/12
摘要： A method for managing distributed computing. The method comprises estimating, for each of a plurality of local computing nodes, a distribution of multidimensional values in a space. Each multidimensional value is calculated according to a plurality of locally monitored parameters. The method further includes calculating safe zones in the space where each safe zone is defined according to a respective estimated distribution under a global geometric constraint in the space and setting local geometric constraints for the local computing nodes according to the respective safe zones. Each local geometric constraint is defined such that a detection of at least one monitored multidimensional value violating it by a respective local computing node induces a communication event between the respective local computing node and one or more central computing nodes.
摘要翻译：一种用于管理分布式计算的方法。该方法包括为多个本地计算节点中的每一个估计空间中的多维值的分布。根据多个本地监视的参数来计算每个多维值。该方法还包括根据空间中的全局几何约束下的相应估计分布来计算在每个安全区域的空间中的安全区域，并根据相应的安全区域为本地计算节点设置局部几何约束。定义每个局部几何约束使得由相应的本地计算节点检测至少一个被监视的多维值的检测引起相应的本地计算节点和一个或多个中央计算节点之间的通信事件。

6. 发明申请

US20100325265A1 METHOD AND SYSTEM OF MANAGING AND/OR MONITORING DISTRIBUTED COMPUTING BASED ON GEOMETRIC CONSTRAINTS 有权
标题翻译：基于几何约束的管理和/或监控分布式计算的方法和系统
公开(公告)号：US20100325265A1
公开(公告)日：2010-12-23
申请号：US12817242
申请日：2010-06-17
申请人： Assaf SCHUSTER , Daniel Keren , Guy Sagy , Izchak Sherfman
发明人： Assaf SCHUSTER , Daniel Keren , Guy Sagy , Izchak Sherfman
IPC分类号： G06F15/16
CPC分类号： H04L67/125 , G06F11/3006 , G06F11/3058 , H04L67/12
摘要： A method for managing distributed computing. The method comprises estimating, for each of a plurality of local computing nodes, a distribution of multidimensional values in a space. Each multidimensional value is calculated according to a plurality of locally monitored parameters. The method further includes calculating safe zones in the space where each safe zone is defined according to a respective estimated distribution under a global geometric constraint in the space and setting local geometric constraints for the local computing nodes according to the respective safe zones. Each local geometric constraint is defined such that a detection of at least one monitored multidimensional value violating it by a respective local computing node induces a communication event between the respective local computing node and one or more central computing nodes.
摘要翻译：一种用于管理分布式计算的方法。该方法包括为多个本地计算节点中的每一个估计空间中的多维值的分布。根据多个本地监视的参数来计算每个多维值。该方法还包括根据空间中的全局几何约束下的相应估计分布来计算在每个安全区域的空间中的安全区域，并根据相应的安全区域为本地计算节点设置局部几何约束。定义每个局部几何约束使得由相应的本地计算节点检测至少一个被监视的多维值的检测引起相应的本地计算节点和一个或多个中央计算节点之间的通信事件。

7. 发明授权

US06501857B1 Method and system for detecting and classifying objects in an image 有权
标题翻译：用于检测和分类图像中物体的方法和系统
公开(公告)号：US06501857B1
公开(公告)日：2002-12-31
申请号：US09357692
申请日：1999-07-20
申请人： Craig Gotsman , Daniel Keren , Michael Elad
发明人： Craig Gotsman , Daniel Keren , Michael Elad
IPC分类号： G06K900
CPC分类号： G06F17/30247 , G06K9/00228 , G06K9/6232 , Y10S707/99933 , Y10S707/99936
摘要： This disclosure provides a system for classifying images, used in image detection, image recognition, or other computer vision. The system processes directory images to obtain eigenvectors and eigenvalues, and selects a set of “smooth” basis vectors formed by linear combinations of these eigenvectors to be applied against a target image. Contrary to conventional wisdom, however, a group of the eigenvectors having the weakest eigenvalues are used to select the basis vectors. A second process is then performed on this group of “weakest” eigenvectors to identify a set of candidate vectors, ordered in terms of “smoothness.” The set of basis vectors (preferably 3-9) is then chosen from the candidate vectors in order of smoothness, which are then applied in an image detection or image recognition process. Unlike some conventional systems where “strong” directory presence and thresholds are used to detect possible matches, the present system uses smooth, weak vectors to ideally produce zero or near zero results for matches.
摘要翻译：本公开提供了一种用于对图像进行分类的系统，用于图像检测，图像识别或其他计算机视觉。该系统处理目录图像以获得特征向量和特征值，并且选择一组由要应用于目标图像的特征向量的线性组合形成的“平滑”基向量。然而，与常规智慧相反，使用具有最弱特征值的一组特征向量来选择基本向量。然后对这组“最弱”特征向量进行第二个处理，以识别一组以“平滑度”排列的候选向量。然后从平滑度的顺序中从候选向量中选择一组基向量（优选3-9），然后将其应用于图像检测或图像识别处理。与使用“强”目录存在和阈值来检测可能的匹配的一些常规系统不同，本系统使用平滑的弱向量来理想地产生零或接近零的匹配结果。

8. 发明授权

US06628834B2 Template matching system for images 失效
标题翻译：图像模板匹配系统
公开(公告)号：US06628834B2
公开(公告)日：2003-09-30
申请号：US10193077
申请日：2002-07-11
申请人： Craig Gotsman , Daniel Keren , Michael Elad
发明人： Craig Gotsman , Daniel Keren , Michael Elad
IPC分类号： G06K962
CPC分类号： G06F17/30247 , G06K9/00228 , G06K9/6232 , Y10S707/99933 , Y10S707/99936
摘要： This disclosure provides a system for classifying images, used in image detection, image recognition, or other computer vision. The system processes directory images to obtain eigenvectors and eigenvalues, and selects a set of “smooth” basis vectors formed by linear combinations of these eigenvectors to be applied against a target image. Contrary to conventional wisdom, however, a group of the eigenvectors having the weakest eigenvalues are used to select the basis vectors. A second process is then performed on this group of “weakest” eigenvectors to identify a set of candidate vectors, ordered in terms of “smoothness.” The set of basis vectors (preferably 3-9) is then chosen from the candidate vectors in order of smoothness, which are then applied in an image detection or image recognition process. Unlike some conventional systems where “strong” directory presence and thresholds are used to detect possible matches, the present system uses smooth, weak vectors to ideally produce zero or near zero results for matches.
摘要翻译：本公开提供了一种用于对图像进行分类的系统，用于图像检测，图像识别或其他计算机视觉。该系统处理目录图像以获得特征向量和特征值，并且选择一组由要应用于目标图像的特征向量的线性组合形成的“平滑”基向量。然而，与常规智慧相反，使用具有最弱特征值的一组特征向量来选择基本向量。然后对这组“最弱”特征向量进行第二个处理，以识别一组以“平滑度”排列的候选向量。然后从平滑度的顺序中从候选向量中选择一组基向量（优选3-9），然后将其应用于图像检测或图像识别处理。与使用“强”目录存在和阈值来检测可能的匹配的一些常规系统不同，本系统使用平滑的弱向量来理想地产生零或接近零的匹配结果。

9. 发明授权

US06625305B1 Image demosaicing method 失效
标题翻译：图像去马赛克法
公开(公告)号：US06625305B1
公开(公告)日：2003-09-23
申请号：US09375178
申请日：1999-08-16
申请人： Daniel Keren
发明人： Daniel Keren
IPC分类号： H04N315
CPC分类号： G06T3/4015 , H04N9/045
摘要： A method for operating a data processing system to generate a second image from a first image having partially sampled color values at each pixel. The first image includes a two-dimensional array of pixel values, each of the pixel values corresponding to the light intensity in one of a plurality of spectral bands at a location in the first image. The second image includes a second two-dimensional array of color vectors. Each color vector has a light intensity value for each of the spectral bands. There is one such vector corresponding to each location having a pixel value in the first image. One component of the vector is equal to the pixel value in the first image at that location. The present invention computes the missing color components at each location. The method begins by providing an estimate for each component that is not equal to one of the pixel values from the first image for each vector. An updated estimate for each of the estimates is then generated by optimizing a weighted sum of first and second functions. The first function measures the degree of roughness of the second image, and the second function measures the degree to which the vectors change direction between neighboring locations in the second image.
摘要翻译：一种用于操作数据处理系统以从具有在每个像素处具有部分采样的颜色值的第一图像生成第二图像的方法。第一图像包括像素值的二维阵列，每个像素值对应于在第一图像中的位置处的多个光谱带之一中的光强度。第二图像包括彩色矢量的第二二维阵列。每个彩色矢量具有每个光谱带的光强度值。存在对应于在第一图像中具有像素值的每个位置的一个这样的向量。矢量的一个分量等于该位置的第一个图像中的像素值。本发明计算每个位置处的缺失颜色分量。该方法开始于为每个向量的第一图像提供不等于像素值之一的每个分量的估计。然后通过优化第一和第二功能的加权和来生成每个估计的更新的估计。第一函数测量第二图像的粗糙度，第二函数测量矢量在第二图像中的相邻位置之间改变方向的程度。

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