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31.发明授权Decoding of embedded bit streams produced by context-based ordering and coding of transform coeffiecient bit-planes 有权对基于上下文的排序和变换系数位平面的编码产生的嵌入式位流的解码公开(公告)号：US06510247B1
公开(公告)日：2003-01-21
申请号：US09213743
申请日：1998-12-17
IPC分类号： G06K936
CPC分类号： G06T9/007
摘要： A method of decoding an embedded bitstream includes the steps of reading encoded subsequences in the bitstream as ordered, decoding at least some of the ordered subsequences, and combining the subsequences to obtain reconstructed data. The encoded subsequences are read in order of decreasing expected distortion reduction per expected bit of description.
摘要翻译： 一种对嵌入式比特流进行解码的方法包括以下步骤：按顺序读取比特流中的编码子序列，对至少一些有序子序列进行解码，以及组合子序列以获得重构数据。 按照预期的描述位减少预期的失真减少的顺序读取编码的子序列。
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公开(公告)号：US09461872B2
公开(公告)日：2016-10-04
申请号：US12792535
申请日：2010-06-02
CPC分类号： H04L29/08792 , H04L67/12 , H04L69/04
摘要： A distinguished node is dynamically selected from a subset of nodes in a wireless network. Data samples from the subset of nodes are received in view of the distinguished node status. At least one estimate is generated from the data samples and the data samples are compressed conditioned on the estimate.
摘要翻译： 从无线网络中的节点子集中动态地选择识别节点。 考虑到不同的节点状态，接收来自节点子集的数据样本。 从数据样本产生至少一个估计，并且基于估计压缩数据样本。
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公开(公告)号：US20130121062A1
公开(公告)日：2013-05-16
申请号：US13812050
申请日：2010-07-28
CPC分类号： G11C7/10 , G11C7/00 , G11C7/1006 , G11C7/20 , G11C7/22 , G11C13/0002 , G11C13/0069
摘要： A method for rewriting a memory array (408) with a number of memory elements (206) includes performing a rewrite process to change the memory array (408) from an initial state to a target state in a manner that avoids violating to a set of weight constraints at any time during the rewrite process. A memory system includes a memory array (408) and a memory controller (104) configured to perform a rewrite process to change the memory array (408) from an initial state to a target state in a manner that avoids violating a set of weight constraints at any time during the rewrite process.
摘要翻译： 一种用多个存储元件（206）重写存储器阵列（408）的方法包括执行重写过程以将存储器阵列（408）从初始状态改变到目标状态，以避免违反一组 在重写过程中的任何时候的权重约束。 存储器系统包括存储器阵列（408）和存储器控制器（104），其被配置为执行改写处理以将存储器阵列（408）从初始状态改变到目标状态，以避免违反一组权重约束 在重写过程中的任何时间。
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34.发明授权公开(公告)号：US08300979B2
公开(公告)日：2012-10-30
申请号：US12511776
申请日：2009-07-29
IPC分类号： G06K9/40
CPC分类号： G06K9/40 , G06K9/6277 , G06T5/002 , G06T2207/20076
摘要： Embodiments of the present invention provide context-class-based universal denoising of noisy images and other noise-corrupted data sets. Prediction-error statistics for each prediction class, relative to a prefiltered image, are collected to estimate a bias for each prediction class, and prediction-error statistics for each conditioning class, relative to a prefiltered image, are accumulated based on the difference between predicted values and corresponding prefiltered-image symbols. The prediction-error statistics are accumulated using computed prediction-error-statistics vectors, with inversion of a prediction-error vector generated from each prediction prior to accumulation in a prediction-error-statistics vector. Conditional probability distributions are computed for individual contexts, which allow for computing a clean-image-estimated, value for each noisy-image value by minimizing a computed distortion over a range of possible estimated-clean-image symbols.
摘要翻译： 本发明的实施例提供了噪声图像和其它噪声损坏的数据集的基于上下文类的通用去噪。 收集每个预测类别相对于预过滤图像的预测误差统计，以估计每个预测类别的偏差，并且基于预测图像之间的差异累积每个调节类别相对于预过滤图像的预测误差统计 值和相应的预过滤图像符号。 使用计算出的预测误差统计量向量累积预测误差统计量，在预测误差统计量向量中积累之前从每个预测产生的预测误差向量的反演。 针对各个上下文计算条件概率分布，其允许通过使可能的估计清洁图像符号的范围上的计算失真最小化来计算每个噪声图像值的干净图像估计值。
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公开(公告)号：US08238290B2
公开(公告)日：2012-08-07
申请号：US12792515
申请日：2010-06-02
IPC分类号： H04W40/00
摘要： A first node receives aggregated compressed data and unaggregated data from a second node in a wireless multi-hop network. The first node compresses its own collected data based on the received unaggregated data. The first node aggregates its own compressed data with the aggregated compressed data received from the second node. The first node forwards an unaggregated version of its own collected data along with aggregated compressed data to a next hop in the wireless multi-hop network.
摘要翻译： 第一节点从无线多跳网络中的第二节点接收聚合压缩数据和未分组数据。 第一个节点根据收到的未分组数据来压缩自己收集的数据。 第一个节点将其自己的压缩数据与从第二个节点接收到的聚合压缩数据进行聚合。 第一个节点将其自己收集的数据的集合版本与聚合的压缩数据一起转发到无线多跳网络中的下一跳。
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公开(公告)号：US08189722B2
公开(公告)日：2012-05-29
申请号：US12955860
申请日：2010-11-29
CPC分类号： G11B20/24
摘要： Various embodiments of the present invention relate to a discrete denoiser that replaces symbols in a received, noisy signal with replacement symbols in order to produce a recovered signal less distorted with respect to an originally transmitted, clean signal than the received, noisy signal. Certain, initially developed discrete denoisers employ an analysis of the number of occurrences of metasymbols within the received, noisy signal in order to select symbols for replacement, and to select the replacement symbols for the symbols that are replaced. Denoisers that represent examples of the present invention use blended counts that are combinations of the occurrences of metasymbol families within a noisy signal to determine the symbols to be replaced and the replacement symbols corresponding to them.
摘要翻译： 本发明的各种实施例涉及一种离散去噪器，其使用替换符号替换接收到的噪声信号中的符号，以便产生相比于接收到的噪声信号相对于原始发送的干净信号较不失真的恢复信号。 某些初始开发的离散去噪器采用对接收到的噪声信号中元符号发生次数的分析，以便选择用于替换的符号，并选择替换的符号的替换符号。 代表本发明实例的消泡剂使用作为噪声信号中偶发符号族的出现的组合的混合计数来确定要替换的符号和对应于它们的替换符号。
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公开(公告)号：US07912159B2
公开(公告)日：2011-03-22
申请号：US10765542
申请日：2004-01-26
IPC分类号： H04L27/08
CPC分类号： H03M13/00 , H03M13/47 , H03M13/612
摘要： A method and apparatus for processing a received digital signal that has been corrupted by a channel is disclosed. The method includes storing the received digital signal and receiving a partially corrected sequence of symbols that includes an output of a preliminary denoising system operating on the received digital signal. Information specifying a signal degradation function that measures the signal degradation that occurs if a symbol having the value I is replaced by a symbol having the value J is utilized to generate a processed digital signal by replacing each symbol having a value I in a context of that symbol in the received digital signal with a symbol having a value J if replacement reduces a measure of overall signal degradation in the processed digital signal relative to the received digital signal as measured by the degradation function and the partially corrected sequence of symbols.
摘要翻译： 公开了一种用于处理已经被信道破坏的接收数字信号的方法和装置。 该方法包括存储所接收的数字信号并接收部分校正的符号序列，其包括对所接收的数字信号进行操作的初步去噪系统的输出。 用于指定信号劣化功能的信息，用于测量如果具有值为I的符号被替换为具有值I的符号的情况下发生的信号劣化，则通过替换在该上下文中具有值I的每个符号来代替处理的数字信号 在具有值J的符号的接收数字信号中，如果替换降低了由劣化函数和部分校正的符号序列测量的处理的数字信号中相对于接收的数字信号的整体信号劣化的度量，则符号代表符号。
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38.发明申请CONTEXT-CLUSTER-LEVEL CONTROL OF FILTERING ITERATIONS IN AN ITERATIVE DISCRETE UNIVERSAL DENOISER 失效在迭代离散通用DENOISER中的过滤器的上下文层级控制公开(公告)号：US20110026850A1
公开(公告)日：2011-02-03
申请号：US12512548
申请日：2009-07-30
CPC分类号： G06K9/40 , G06T5/002 , G06T2207/20076
摘要： Embodiments of the present invention are directed to various enhanced discrete-universal denoisers that have been developed to denoise images and other one-dimensional, two-dimensional or higher-dimensional data sets in which the frequency of occurrence of individual contexts may be too low to gather efficient statistical data or context-based symbol prediction. In these denoisers, image quality, signal-to-noise ratios, or other measures of the effectiveness of denoising that would be expected to increase monotonically over a series of iterations may decrease, due to assumptions underlying the discrete-universal-denoising method losing validity. Embodiments of the present invention apply context-class-based statistics and statistical analysis to determine, on a per-context-class basis, when to at least temporarily terminate denoising iterations on each conditioning class. Each iteration of the iterative methods applies context-based denoising only for those conditioning classes that statistical analysis indicates remain valid for denoising purposes.
摘要翻译： 本发明的实施例涉及已经开发用于去噪图像和其他一维二维或更高维数据集的各种增强离散通用去噪器，其中各个上下文的发生频率可能太低到 收集有效的统计数据或基于上下文的符号预测。 在这些去噪器中，由于离散通用去噪方法丧失有效性的假设，图像质量，信噪比或降噪有效性的其他测量值可能会在一系列迭代中单调增加，这可能会降低 。 本发明的实施例应用基于上下文类的统计和统计分析以在每个上下文类的基础上确定何时至少临时终止每个调节类的去噪迭代。 迭代方法的每个迭代都应用基于上下文的去噪，仅针对统计分析指示对于去噪目的有效的那些条件类。
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公开(公告)号：US20110026848A1
公开(公告)日：2011-02-03
申请号：US12511776
申请日：2009-07-29
IPC分类号： G06K9/40
CPC分类号： G06K9/40 , G06K9/6277 , G06T5/002 , G06T2207/20076
摘要： Embodiments of the present invention provide context-class-based universal denoising of noisy images and other noise-corrupted data sets. Prediction-error statistics for each prediction class, relative to a prefiltered image, are collected to estimate a bias for each prediction class, and prediction-error statistics for each conditioning class, relative to a prefiltered image, are accumulated based on the difference between predicted values and corresponding prefiltered-image symbols. The prediction-error statistics are accumulated using computed prediction-error-statistics vectors, with inversion of a prediction-error vector generated from each prediction prior to accumulation in a prediction-error-statistics vector. Conditional probability distributions are computed for individual contexts, which allow for computing a clean-image-estimated, value for each noisy-image value by minimizing a computed distortion over a range of possible estimated-clean-image symbols.
摘要翻译： 本发明的实施例提供了噪声图像和其它噪声损坏的数据集的基于上下文类的通用去噪。 收集每个预测类别相对于预过滤图像的预测误差统计，以估计每个预测类别的偏差，并且基于预测图像之间的差异累积每个调节类别相对于预过滤图像的预测误差统计 值和相应的预过滤图像符号。 使用计算出的预测误差统计量向量累积预测误差统计量，在预测误差统计量向量中积累之前从每个预测产生的预测误差向量的反演。 针对各个上下文计算条件概率分布，其允许通过使可能的估计清洁图像符号的范围上的计算失真最小化来计算每个噪声图像值的干净图像估计值。
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公开(公告)号：US07498961B2
公开(公告)日：2009-03-03
申请号：US11180067
申请日：2005-07-12
申请人： Itschak Weissman , Erik Ordentlich , Gadiel Seroussi , Marcelo Weinberger , Sergio Verdu , Giovanni Motta
发明人： Itschak Weissman , Erik Ordentlich , Gadiel Seroussi , Marcelo Weinberger , Sergio Verdu , Giovanni Motta
IPC分类号： H03M7/00
CPC分类号： G06T5/002 , G06T5/20 , G06T2207/20008 , G06T2207/20032 , G10L21/0208
摘要： Denoising such as discrete universal denoising (DUDE) that scans a noisy signal in an attempt to characterize probabilities of finding symbol values in a particular context in a clean signal can perform a rough denoising on the noisy signal and identify contexts from a roughly denoised signal. The rough denoising improves estimation of the statistical properties of the clean signal by reducing the false differentiation of contexts that noise can otherwise create. Statistical information regarding occurrences of symbols in the noisy signal and corresponding contexts in the roughly denoised signal can then be used to denoise the noisy signal. The specifics of the rough denoising can be chosen based on knowledge of the noise or of the clean data. Alternatively, the DUDE can be used in an iterative fashion where the denoised signal produced from a prior iteration provides the contexts for the next iteration.
摘要翻译： 去噪如离散通用去噪（DUDE），其扫描噪声信号以试图表征在清洁信号中的特定上下文中找到符号值的概率，可对噪声信号执行粗略去噪，并从大致去噪信号中识别上下文。 粗糙去噪通过减少噪声可能产生的上下文的虚假差异来改善干净信号的统计特性的估计。 关于噪声信号中的符号出现的统计信息和粗略去噪信号中的对应上下文可以用于去噪噪声信号。 粗略去噪的细节可以基于噪声或干净数据的知识来选择。 或者，DUDE可以以迭代方式使用，其中从先前迭代产生的去噪信号提供下一次迭代的上下文。
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