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1. 发明授权

US07916958B2 Compression for holographic data and imagery 有权
标题翻译：压缩全息数据和图像
公开(公告)号：US07916958B2
公开(公告)日：2011-03-29
申请号：US12613589
申请日：2009-11-06
申请人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
发明人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
IPC分类号： G06K9/36 , G06K9/76 , G06K9/46
CPC分类号： G06T9/001 , G03H1/08 , G06T9/007
摘要： Image pixel intensity data is transformed to a holographic representation of the image. A subset of the holographic representation is modeled. Model parameters constitute a compressed image representation. A two-dimensional Fourier transform can be applied to obtain the holographic image. Modeling includes applying an analysis portion of an adaptive analysis/synthesis prediction methodology to a subset of the holographic representation. Linear prediction can be the adaptive analysis/synthesis prediction methodology. Prior to modeling, one-dimensional Fourier transform can be performed on the holographic representation and the linear prediction is one-dimensional. Model parameters are preferably quantized. Embodiments include determining error between the model and the model's input data. There the compressed image representation the error, which also can be quantized. The subset of the holographic representation can be less than all the representation. The subset can be a plurality of complete rows; preferably substantially symmetric about 0 Hz.
摘要翻译：图像像素强度数据被转换成图像的全息图像。对全息图的一个子集进行建模。模型参数构成压缩图像表示。可以应用二维傅里叶变换来获得全息图像。建模包括将自适应分析/合成预测方法的分析部分应用于全息表示的子集。线性预测可以是自适应分析/综合预测方法。在建模之前，可以对全息图像进行一维傅里叶变换，并且线性预测是一维的。模型参数优选地被量化。实施例包括确定模型和模型的输入数据之间的误差。有压缩图像表示的错误，也可以量化。全息表示的子集可以小于所有的表示。子集可以是多个完整的行; 优选基本上对称约0Hz。

2. 发明申请

US20100046848A1 Compression For Holographic Data and Imagery 有权
标题翻译：压缩全息数据和图像
公开(公告)号：US20100046848A1
公开(公告)日：2010-02-25
申请号：US12613589
申请日：2009-11-06
申请人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
发明人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
IPC分类号： G06K9/36
CPC分类号： G06T9/001 , G03H1/08 , G06T9/007
摘要： Image pixel intensity data is transformed to a holographic representation of the image. A subset of the holographic representation is modeled. Model parameters constitute a compressed image representation. A two-dimensional Fourier transform can be applied to obtain the holographic image. Modeling includes applying an analysis portion of an adaptive analysis/synthesis prediction methodology to a subset of the holographic representation. Linear prediction can be the adaptive analysis/synthesis prediction methodology. Prior to modeling, one-dimensional Fourier transform can be performed on the holographic representation and the linear prediction is one-dimensional. Model parameters are preferably quantized. Embodiments include determining error between the model and the model's input data. There the compressed image representation the error, which also can be quantized. The subset of the holographic representation can be less than all the representation. The subset can be a plurality of complete rows; preferably substantially symmetric about 0 Hz.
摘要翻译：图像像素强度数据被转换成图像的全息图像。对全息图的一个子集进行建模。模型参数构成压缩图像表示。可以应用二维傅里叶变换来获得全息图像。建模包括将自适应分析/合成预测方法的分析部分应用于全息表示的子集。线性预测可以是自适应分析/综合预测方法。在建模之前，可以对全息图像进行一维傅里叶变换，并且线性预测是一维的。模型参数优选地被量化。实施例包括确定模型和模型的输入数据之间的误差。有压缩图像表示的错误，也可以量化。全息表示的子集可以小于所有的表示。子集可以是多个完整的行; 优选基本上对称约0Hz。

3. 发明授权

US07103537B2 System and method for linear prediction 有权
公开(公告)号：US07103537B2
公开(公告)日：2006-09-05
申请号：US09974091
申请日：2001-10-10
申请人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
发明人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
IPC分类号： G10L19/04 , G06F17/10
CPC分类号： G06K9/0057 , G10L19/04 , G10L25/12
摘要： In a digital signal processor (DSP), input data is configured as a data matrix comprising data samples collected from an input signal. A weight vector is applied to the data matrix, where the weight vector comprises three parts including (a) a rank reduction transformation produced by decomposition of the data samples in a multistage Wiener filter having a plurality of stages, each stage comprising projection onto two subspaces. Each subsequent stage comprises projecting data transformed by the preceding second subspace onto each of a first subspace comprising a normalized cross-correlation vector at the previous stage and a second subspace comprising the null space of the normalized cross-correlation vector of the current stage, to form a reduced rank data matrix. Part (b) of the weight vector comprises minimizing the mean squared error in the reduced rank data space. The output is a linear estimate of the input data. In one embodiment, further processing produces an estimate of the power spectral density of the input signal.

4. 发明授权

US07426463B2 System and method for linear prediction 有权
标题翻译：线性预测的系统和方法
公开(公告)号：US07426463B2
公开(公告)日：2008-09-16
申请号：US11496419
申请日：2006-08-01
申请人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
发明人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
IPC分类号： G10L19/04 , G10L19/14
CPC分类号： G06K9/0057 , G10L19/04 , G10L25/12
摘要： In a digital signal processor (DSP), input data is configured as a data matrix comprising data samples collected from an input signal. A weight vector is applied to the matrix, where the weight vector comprises three parts including (a) a rank reduction transformation produced by decomposition of data samples in a multistage Wiener filter having a plurality of stages, each stage comprising projection onto two subspaces. Each subsequent stage comprises projecting data transformed by the preceding second subspace onto each of a first subspace comprising a normalized cross-correlation vector at the previous stage and a second subspace comprising the null space of the normalized cross-correlation vector of the current stage, to form a reduced rank data matrix. Part (b) of the weight vector comprises minimizing mean squared error in the reduced rank data space. The output is a linear estimate of input data.
摘要翻译：在数字信号处理器（DSP）中，输入数据被配置为包括从输入信号收集的数据样本的数据矩阵。权重向量被应用于矩阵，其中权重向量包括三个部分，其包括（a）通过在具有多个级的多级维纳滤波器中对数据样本进行分解而产生的秩缩减变换，每个级包括投影到两个子空间上。每个后续阶段包括将由前面的第二子空间变换的数据投影到包括前一级的归一化互相关向量的第一子空间和包括当前阶段的归一化互相关向量的零空间的第二子空间，形成一个降级数据矩阵。权重向量的部分（b）包括最小化等级数据空间中的均方误差。输出是输入数据的线性估计。

5. 发明授权

US07653248B1 Compression for holographic data and imagery 有权
标题翻译：压缩全息数据和图像
公开(公告)号：US07653248B1
公开(公告)日：2010-01-26
申请号：US11267177
申请日：2005-11-07
申请人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
发明人： Hanna Elizabeth Witzgall , Jay Scott Goldstein
IPC分类号： G06K9/76 , G06K9/36 , G06K9/46
CPC分类号： G06T9/001 , G03H1/08 , G06T9/007
摘要： Image pixel intensity data is transformed to a holographic representation of the image. A subset of the holographic representation is modeled. Model parameters constitute a compressed image representation. A two-dimensional Fourier transform can be applied to obtain the holographic image. Modeling includes applying an analysis portion of an adaptive analysis/synthesis prediction methodology to a subset of the holographic representation. Linear prediction can be the adaptive analysis/synthesis prediction methodology. Prior to modeling, one-dimensional Fourier transform can be performed on the holographic representation and the linear prediction is one-dimensional. Model parameters are preferably quantized. Embodiments include determining error between the model and the model's input data. There the compressed image representation the error, which also can be quantized. The subset of the holographic representation can be less than all the representation. The subset can be a plurality of complete rows; preferably substantially symmetric about 0 Hz.
摘要翻译：图像像素强度数据被转换成图像的全息图像。对全息图的一个子集进行建模。模型参数构成压缩图像表示。可以应用二维傅里叶变换来获得全息图像。建模包括将自适应分析/合成预测方法的分析部分应用于全息表示的子集。线性预测可以是自适应分析/综合预测方法。在建模之前，可以对全息图像进行一维傅里叶变换，并且线性预测是一维的。模型参数优选地被量化。实施例包括确定模型和模型的输入数据之间的误差。有压缩图像表示的错误，也可以量化。全息表示的子集可以小于所有的表示。子集可以是多个完整的行; 优选基本上对称约0Hz。

6. 发明授权

US08422799B1 Complex image compression 有权
标题翻译：复杂的图像压缩
公开(公告)号：US08422799B1
公开(公告)日：2013-04-16
申请号：US12004027
申请日：2007-12-20
申请人： Hanna Elizabeth Witzgall , Timothy F. Settle
发明人： Hanna Elizabeth Witzgall , Timothy F. Settle
IPC分类号： G06K9/36
CPC分类号： G06T9/004 , G06T9/001 , G06T9/007
摘要： Complex image data is transformed to a holographic representation of the image. A subset of the holographic representation is modeled. Model parameters constitute a compressed image representation. A two-dimensional Fourier transform can be applied to obtain the holographic image. Modeling includes applying an analysis portion of an adaptive analysis/synthesis linear prediction methodology to a subset of the holographic representation to obtain an autoregressive model. Prior to modeling, one-dimensional Fourier transform can be performed on the holographic representation and the linear prediction is one-dimensional. Model parameters are preferably quantized. Embodiments include determining error between the model and the model's input data. There the compressed image representation the error, which also can be quantized. The subset of the holographic representation can be less than all the representation. The subset can be a plurality of complete rows; preferably substantially symmetric about 0 Hz.
摘要翻译：复杂图像数据被转换成图像的全息图像。对全息图的一个子集进行建模。模型参数构成压缩图像表示。可以应用二维傅里叶变换来获得全息图像。建模包括将自适应分析/合成线性预测方法的分析部分应用于全息图像的子集以获得自回归模型。在建模之前，可以对全息图像进行一维傅里叶变换，并且线性预测是一维的。模型参数优选地被量化。实施例包括确定模型和模型的输入数据之间的误差。有压缩图像表示的错误，也可以量化。全息表示的子集可以小于所有的表示。子集可以是多个完整的行; 优选基本上对称约0Hz。

7. 发明授权

US08422798B1 Magnitude image compression 有权
标题翻译：幅度图像压缩
公开(公告)号：US08422798B1
公开(公告)日：2013-04-16
申请号：US11898763
申请日：2007-09-14
申请人： Hanna Elizabeth Witzgall
发明人： Hanna Elizabeth Witzgall
IPC分类号： G06K9/36 , G06K9/46
CPC分类号： G06T9/007
摘要： Embodiments of the invention view image intensity data as a spectrum of underlying wave forms. The spectrum of these waves can be approximated using spectral estimation techniques where the spectrum parameters constitute the compressed image. The image's underlying wave forms can be recovered using an inverse Fourier transform. The original image can also be symmetrically extended prior to the transform to preserve real valued transformed data and model parameters. The modeling method is typically based on a linear predictive methodology to obtain the spectrum parameters. Other transforms include a 2-D Fourier transform that transforms the image into a holographic representation similar to synthetic aperture radar (SAR) phase history. This 2-D waveform holographic format can be decorrelated into 1-D planar waves by applying a 1D Fourier transform. This process enables 1-D linear predictive modeling to obtain the spectral parameters. For compression applications the model parameters are preferably quantized.
摘要翻译：本发明的实施例将图像强度数据视为基础波形的频谱。可以使用频谱估计技术近似这些波的频谱，其中频谱参数构成压缩图像。图像的底层波形可以使用逆傅立叶变换进行恢复。原始图像也可以在变换之前对称扩展，以保留实值变换的数据和模型参数。建模方法通常基于获得频谱参数的线性预测方法。其他变换包括将图像变换成类似于合成孔径雷达（SAR）相位历史的全息表示的二维傅里叶变换。通过应用1D傅立叶变换，该2-D波形全息格式可以解相关成1-D平面波。该过程使得能够获得光谱参数的1-D线性预测建模。对于压缩应用，模型参数优选地被量化。

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