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1.发明申请SYSTEM AND METHODS FOR COMPUTING FORWARD AND INVERSE DISCRETE PERIODIC RADON TRANSFORM 审中-公开用于计算前向和反向离散周期性RADON变换的系统和方法公开(公告)号：US20160314603A1
公开(公告)日：2016-10-27
申请号：US15103977
申请日：2014-12-15
Applicant: STC.UNM
Inventor： Cesar Carranza , Marios Stephanou Pattichis , Daniel Llamocca Obregon
CPC classification number: G06T11/006 , G06F17/14 , G06F17/141 , G06K9/00973 , G06T2211/428
Abstract: A fast and a scalable approach for computing the forward and inverse DPRT that uses: (i) a parallel array of fixed-point adder trees to compute the additions, (ii) circular shift registers to remove the need for accessing external memory components, (iii) an image block-based approach to DPRT computation that can fit the proposed architecture to available resources, and (iv) fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image.
Abstract translation: 用于计算正向和反向DPRT的快速和可扩展的方法，其使用：（i）用于计算加法的定点加法器树的并行阵列，（ii）循环移位寄存器以消除访问外部存储器组件的需要， iii）基于图像块的DPRT计算方法，其可以将所提出的架构适合于可用资源，以及（iv）在不依赖于输入图像的大小的一个或几个时钟周期内计算的快速转置。
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公开(公告)号：US10949985B2
公开(公告)日：2021-03-16
申请号：US16096843
申请日：2017-06-02
Applicant: STC.UNM
Abstract: An AM-FM representation is used to derive AM and FM based equations that can be applied to two consecutive frames in parallel to derive motion estimates. The multidimensional AM-FM representations provide general representations of non-stationary content in digital images. The AM-FM estimate captures single images and features of a video that can lead to different applications in image and video analysis, for example, computer-aided diagnosis in medical applications or monitoring micro-movements of rocky material in the pit slopes.
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公开(公告)号：US10810696B2
公开(公告)日：2020-10-20
申请号：US15780052
申请日：2016-12-16
Applicant: STC.UNM
Inventor： Marios Stephanou Pattichis , Cesar Carranza , Daniel Llamocca Obregon
Abstract: Fast and scalable architectures and methods adaptable to available resources, that (1) compute 2-D convolutions using 1-D convolutions, (2) provide fast transposition and accumulation of results for computing fast cross-correlations or 2-D convolutions, and (3) provide parallel computations using pipelined 1-D convolvers. Additionally, fast and scalable architectures and methods that compute 2-D linear convolutions using Discrete Periodic Radon Transforms (DPRTs) including the use of scalable DPRT, Fast DPRT, and fast 1-D convolutions.
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公开(公告)号：US11076153B2
公开(公告)日：2021-07-27
申请号：US15747982
申请日：2016-07-31
Applicant: STC.UNM
Inventor： Marios Stephanou Pattichis , Yuebing Jiang , Cong Zong , Gangadharan Esakki , Venkatesh Jatla , Andreas Panayides
IPC: H04N19/127 , H04N19/172 , H04N19/149 , H04N19/119 , H04N19/126 , H04N19/147
Abstract: System and methods for the joint control of reconstructed video quality, computational complexity and compression rate for intra-mode and inter-mode video encoding in HEVC. The invention provides effective methods for (i) generating a Pareto front for intra-coding by varying CTU parameters and the QP, (ii) generating a Pareto front for inter-coding by varying GOP configurations and the QP, (iii) real-time and offline Pareto model front estimation using regression methods, (iv) determining the optimal encoding configurations based on the Pareto model by root finding and local search, and (v) robust adaptation of the constraints and model updates at both the CTU and GOP levels.
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公开(公告)号：US09542198B2
公开(公告)日：2017-01-10
申请号：US14791627
申请日：2015-07-06
Applicant: STC.UNM
CPC classification number: G06F9/4401 , G06F17/5054 , G06F2217/08 , H03H17/0241 , H03H17/0294 , H03H17/06 , H04N19/625
Abstract: A dynamically reconfigurable framework manages processing applications in order to meet time-varying constraints to select an optimal hardware architecture. The optimal architecture satisfies time-varying constraints including for example, supplied power, required performance, accuracy levels, available bandwidth, and quality of output such as image reconstruction. The process of determining an optimal solution is defined in terms of multi-objective optimization using Pareto-optimal realizations.
Abstract translation: 动态可重构框架管理处理应用程序，以便满足时变约束以选择最佳硬件体系结构。 最优架构满足时变约束，包括例如所提供的功率，所需性能，精度水平，可用带宽以及诸如图像重建的输出质量。 确定最优解的过程是使用帕累托最优实现的多目标优化来定义的。
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Patent Agency Ranking
公开(公告)号：US20140165021A1
公开(公告)日：2014-06-12
申请号：US14069822
申请日：2013-11-01
Applicant: STC.UNM
IPC: G06F17/50
CPC classification number: G06F9/4401 , G06F17/5054 , G06F2217/08 , H03H17/0241 , H03H17/0294 , H03H17/06 , H04N19/625
Abstract: A dynamically reconfigurable framework manages processing applications in order to meet time-varying constraints to select an optimal hardware architecture. The optimal architecture satisfies time-varying constraints including for example, supplied power, required performance, accuracy levels, available bandwidth, and quality of output such as image reconstruction. The process of determining an optimal solution is defined in terms of multi-objective optimization using Pareto-optimal realizations.
Abstract translation: 动态可重构框架管理处理应用程序，以便满足时变约束以选择最佳硬件体系结构。 最优架构满足时变约束，包括例如所提供的功率，所需性能，精度水平，可用带宽以及诸如图像重建的输出质量。 确定最优解的过程是使用帕累托最优实现的多目标优化来定义的。
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公开(公告)号：US10943322B2
公开(公告)日：2021-03-09
申请号：US15780076
申请日：2016-12-16
Applicant: STC.UNM
Inventor： Marios Stephanou Pattichis , Cesar Carranza , Daniel Llamocca Obregon
Abstract: Fast and a scalable algorithms and methods adaptable to available resources for computing (1) the DPRT on multicore CPUs by distributing the computation of the DPRT primary directions among the different cores, and (2) the DPRT on GPUs using parallel, distributed, and synchronized ray computations among the GPU cores with “ray” referring to one of the sums required for computing the DPRT or its inverse along a prime direction.
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公开(公告)号：US10049469B2
公开(公告)日：2018-08-14
申请号：US15103977
申请日：2014-12-15
Applicant: STC.UNM
Inventor： Cesar Carranza , Marios Stephanou Pattichis , Daniel Llamocca Obregon
Abstract: A fast and a scalable approach for computing the forward and inverse DPRT that uses: (i) a parallel array of fixed-point adder trees to compute the additions, (ii) circular shift registers to remove the need for accessing external memory components, (iii) an image block-based approach to DPRT computation that can fit the proposed architecture to available resources, and (iv) fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image.
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公开(公告)号：US09111059B2
公开(公告)日：2015-08-18
申请号：US14069822
申请日：2013-11-01
Applicant: STC.UNM
CPC classification number: G06F9/4401 , G06F17/5054 , G06F2217/08 , H03H17/0241 , H03H17/0294 , H03H17/06 , H04N19/625
Abstract: A dynamically reconfigurable framework manages processing applications in order to meet time-varying constraints to select an optimal hardware architecture. The optimal architecture satisfies time-varying constraints including for example, supplied power, required performance, accuracy levels, available bandwidth, and quality of output such as image reconstruction. The process of determining an optimal solution is defined in terms of multi-objective optimization using Pareto-optimal realizations.
Abstract translation: 动态可重构框架管理处理应用程序，以便满足时变约束以选择最佳硬件体系结构。 最优架构满足时变约束，包括例如所提供的功率，所需性能，精度水平，可用带宽以及诸如图像重建的输出质量。 确定最优解的过程是使用帕累托最优实现的多目标优化来定义的。
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公开(公告)号：US20190139234A1
公开(公告)日：2019-05-09
申请号：US16096843
申请日：2017-06-02
Applicant: STC.UNM
Abstract: An AM-FM representation is used to derive AM and FM based equations that can be applied to two consecutive frames in parallel to derive motion estimates. The multidimensional AM-FM representations provide general representations of non-stationary content in digital images. The AM-FM estimate captures single images and features of a video that can lead to different applications in image and video analysis, for example, computer-aided diagnosis in medical applications or monitoring micro-movements of rocky material in the pit slopes.
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