System for interactive visualization and analysis of imaging spectrometry datasets over a wide-area network
    1.
    发明授权
    System for interactive visualization and analysis of imaging spectrometry datasets over a wide-area network 失效
    用于在广域网上进行成像光谱数据集的交互式可视化和分析的系统

    公开(公告)号:US06546146B1

    公开(公告)日:2003-04-08

    申请号:US09182187

    申请日:1998-10-30

    IPC分类号: G06K936

    CPC分类号: G06T9/008

    摘要: The present invention relates to a method of viewing and processing hyper-spectral image data compressed using a VQ algorithm. According to the invention the data is compressed using a codebook of codevectors including binary spectral vectors, which allows processing of the compressed data and viewing of data within a datacube without expanding the compressed data into the complete datacube. In order to view an image derived from a datacube, for each pixel within the image a location within the datacube is selected, an index value from the index map at that location is retrieved, and a spectral value from a spectral vector within the codebook is retrieved for said pixel, the spectral vector identified by the retrieved index. A single spectral vector is easily viewed by displaying a spectral vector from the codebook.

    摘要翻译: 本发明涉及一种使用VQ算法压缩的超光谱图像数据的查看和处理方法。 根据本发明,使用包括二进制频谱矢量在内的代码矢量码本对数据进行压缩,这允许压缩数据的处理和数据存储器内的数据的查看,而不将压缩的数据扩展到完整的数据存储器中。 为了查看从数据库导出的图像,对于图像内的每个像素,选择数据库内的位置,从该位置处的索引图中检索索引值,并且从码本内的频谱矢量的频谱值为 对于所述像素检索,由所检索的索引识别的频谱矢量。 通过从码本显示光谱矢量,可以容易地观看单个光谱矢量。

    Method and system for compressing a continuous data flow in real-time using recursive hierarchical self-organizing cluster vector quantization (HSOCVQ)
    2.
    发明授权
    Method and system for compressing a continuous data flow in real-time using recursive hierarchical self-organizing cluster vector quantization (HSOCVQ) 失效
    使用递归分层自组织簇矢量量化(HSOCVQ)实时压缩连续数据流的方法和系统,

    公开(公告)号:US06798360B1

    公开(公告)日:2004-09-28

    申请号:US10606761

    申请日:2003-06-27

    IPC分类号: H03M700

    CPC分类号: H03M7/3082

    摘要: The present invention relates to a method for compressing a continuous data flow based on lossy compression. In real-time data compression, a series of data subsets acquired in a given period of time are treated as a regional data cube for the purpose of dividing a continuous series of data subsets into a plurality of data cubes. Reuse of existing codevectors is important in achieving high compression performance. For encoding spectral vectors on a subset-by-subset basis in a current region two types of codevectors are used, codevectors that have been newly trained for previous data subsets in the current region and codevectors trained for the previous region. The problem of a visible spatial boundary between two adjacent regions after decompression is overcome by reusing the codevectors trained from a previous region to encode the spectral vectors in the current region in order to attain a seamless conjunction of the two adjacent regions. Experimental results show that the method for compressing a continuous data flow in real-time according to the present invention performs as well as data compression performed in batch mode. Therefore, the method is highly advantageous in, for example, space applications or medical imaging.

    摘要翻译: 本发明涉及一种基于有损压缩来压缩连续数据流的方法。 在实时数据压缩中,在给定时间段内获取的一系列数据子集被视为区域数据立方体,用于将连续的一系列数据子集划分成多个数据立方体。 现有代码示例的重用对于实现高压缩性能很重要。 为了在当前区域中以子集为基础对频谱矢量进行编码,使用两种类型的码矢量,已经针对当前区域中的先前数据子集新近训练的码矢量,以及针对先前区域训练的码矢量。 解压缩后两个相邻区域之间的可见空间边界的问题通过重用来自先前区域训练的码矢来克服当前区域中的频谱矢量,以便获得两个相邻区域的无缝连接。 实验结果表明,根据本发明实时压缩连续数据流的方法以批处理方式执行数据压缩。 因此,该方法在例如空间应用或医学成像方面是非常有利的。

    Data compression engines and real-time wideband compressor for multi-dimensional data
    3.
    发明授权
    Data compression engines and real-time wideband compressor for multi-dimensional data 失效
    数据压缩引擎和实时宽带压缩器用于多维数据

    公开(公告)号:US07251376B2

    公开(公告)日:2007-07-31

    申请号:US10651110

    申请日:2003-08-29

    IPC分类号: G06K9/36 G06K9/46

    摘要: The present invention relates to a real-time wideband compressor for multi-dimensional data. The compressor comprises a plurality of compression engines for simultaneously compressing a plurality of data subsets of a set of input data vectors and providing compressed data thereof using one of SAMVQ or HSOCVQ data compression. Each compression engine comprises an along spectral vectors codevector trainer as well as an across spectral bands codevector trainer. The compression engines are programmable to perform either along spectral vectors codevector training or across spectral bands codevector training in combination with one of the SAMVQ or HSOCVQ techniques without changing hardware. The compressor further comprises a network switch for partitioning the set of input data vectors into the plurality of data subsets, for providing each of the plurality of data subsets to one of the plurality of compression engines, and for transmitting the compressed data. The real-time wideband compressor is highly advantageous in, for example, space applications by programmable enabling performance of different techniques of codevector training as well as different techniques of VQ. Furthermore, after the compression process is started the compression process is performed autonomously without external communication.

    摘要翻译: 本发明涉及用于多维数据的实时宽带压缩器。 压缩机包括多个压缩引擎,用于同时压缩一组输入数据向量的多个数据子集,并使用SAMVQ或HSOCVQ数据压缩之一提供其压缩数据。 每个压缩引擎包括沿着频谱矢量码矢量训练器以及跨频谱带码矢量训练器。 压缩引擎可编程为可以在不改变硬件的情况下,沿着频谱矢量码矢量训练或跨频谱频带编码矢量训练与SAMVQ或HSOCVQ技术中的一种进行组合。 该压缩器还包括网络交换机,用于将该组输入数据向量划分成多个数据子集,用于将多个数据子集中的每一个提供给多个压缩引擎中的一个,并用于发送压缩数据。 实时宽带压缩器在例如空间应用中通过可编程实现不同技术的码向量训练以及不同的VQ技术是非常有利的。 此外,在压缩处理开始之后,压缩处理在没有外部通信的情况下自主地执行。

    Method of coding a continuous data flow using vector quantization
    4.
    发明授权
    Method of coding a continuous data flow using vector quantization 有权
    使用向量量化对连续数据流进行编码的方法

    公开(公告)号:US07801365B2

    公开(公告)日:2010-09-21

    申请号:US12453426

    申请日:2009-05-11

    IPC分类号: G06K9/36 G06K9/00 H04B1/66

    CPC分类号: G06T9/008

    摘要: Methods and systems for compressing a continuous data flow for numerous applications where it is necessary to process large data sets such as hyper-spectral data cubes in real-time. A predetermined number of 2D focal plane frames in a boundary area of a previous regional data cube close to a current regional data cube are included in a training set used for codevector training for the current region. Therefore, no artificial boundary occurs between the two adjacent regions when codevectors trained in this way are used for codebook generation and encoding of the spectral vectors of the current regional data cube. This process substantially reduces image artifacts between adjacent regions. A remedy for the single bit error problem is also provided. Full redundancy of compressed data for a regional data cube is obtained by combining a previous regional data cube and the current regional data cube for codebook training. In order to obtain redundancy for the index map, the codebook is used to encode the current regional data cube as well as the previous regional data cube producing a baseline index map for the current regional data cube and a redundant index map for the previous regional data cube. Therefore, full redundancy for a regional data cube is provided allowing restoration of a regional data cube even if its codebook and/or index map are corrupted or lost due to single bit errors.

    摘要翻译: 用于压缩多个应用的​​连续数据流的方法和系统,其中需要实时处理诸如超光谱数据立方体之类的大数据集。 接近当前区域数据立方体的先前区域数据立方体的边界区域中的预定数量的2D焦平面帧被包括在用于当前区域的码矢量训练的训练集中。 因此,当以这种方式训练的代码矢量用于当前区域数据立方体的频谱矢量的码本生成和编码时,两个相邻区域之间不会发生人为边界。 该过程基本上减少相邻区域之间的图像伪像。 还提供了单位错误问题的补救措施。 通过组合先前的区域数据立方体和当前用于码本训练的区域数据立方体,获得区域数据立方体的压缩数据的完全冗余度。 为了获得索引图的冗余,码本用于对当前区域数据立方体以及以前的区域数据立方体进行编码,以生成当前区域数据立方体的基线索引图,以及用于先前区域数据的冗余索引图 立方体。 因此,提供区域数据立方体的完全冗余,允许恢复区域数据立方体,即使其码本和/或索引映射由于单个位错误而损坏或丢失。

    System and method for encoding multidimensional data using hierarchical self-organizing cluster vector quantization
    5.
    发明授权
    System and method for encoding multidimensional data using hierarchical self-organizing cluster vector quantization 失效
    使用分层自组织聚类向量量化对多维数据进行编码的系统和方法

    公开(公告)号:US06724940B1

    公开(公告)日:2004-04-20

    申请号:US09725370

    申请日:2000-11-24

    IPC分类号: G06K936

    CPC分类号: H04N19/94

    摘要: The present invention relates to a method of encoding a hyper-spectral image datacube using vector quantization. According to the invention, a temporary codebook having a small number, n, of codevectors is generated from the datacube. The datacube is processed using the temporary codebook to form n clusters (subsets) of vectors. A codevector corresponds to a cluster and is the centre of gravity for the cluster. In the compression process, vectors in each cluster are encoded by the corresponding codevector. Then the reconstruction fidelity of the encoded cluster is evaluated. When the fidelity of an encoded cluster is better than a predetermined fidelity, the codevector relating to that cluster is stored in a final codebook and the vectors in the cluster are expressed with the index (address) of the codevector in the final codebook. When the fidelity of an encoded cluster is not suitable, the cluster is reencoded with a new temporary codebook generated from this cluster, and the same process is repeated. The compression process is recursively implemented until all clusters are processed.

    摘要翻译: 本发明涉及使用矢量量化对超光谱图像数据库进行编码的方法。 根据本发明,从数据存储器生成具有小数目n个码矢量的临时码本。 使用临时码本处理数据存储区以形成向量的n个簇(子集)。 码矢量对应于一个群集,是群集的重心。 在压缩过程中,每个簇中的向量由相应的码向量编码。 然后评估编码簇的重建保真度。 当编码簇的保真度比预定的保真度更好时,与该簇相关的码矢量被存储在最终的码本中,并且簇中的向量用最终码本中的码矢量的索引(地址)表示。 当编码集群的保真度不合适时,集群将使用从该集群生成的新临时代码簿进行重新编码,并重复相同的过程。 压缩过程被递归地实现,直到所有的簇被处理。

    Codevector trainers and real-time compressor for multi-dimensional data
    6.
    发明授权
    Codevector trainers and real-time compressor for multi-dimensional data 失效
    Codevector培训师和多维数据的实时压缩器

    公开(公告)号:US08107747B2

    公开(公告)日:2012-01-31

    申请号:US11812948

    申请日:2007-06-22

    IPC分类号: G06K9/36 G06K9/46

    摘要: The present invention relates to a real-time wideband compressor for multi-dimensional data. The compressor comprises a plurality of compression engines for simultaneously compressing a plurality of data subsets of a set of input data vectors and providing compressed data thereof using one of SAMVQ or HSOCVQ data compression. Each compression engine comprises an along spectral vectors codevector trainer as well as an across spectral bands codevector trainer. The compression engines are programmable to perform either along spectral vectors codevector training or across spectral bands codevector training in combination with one of the SAMVQ or HSOCVQ techniques without changing hardware. The compressor further comprises a network switch for partitioning the set of input data vectors into the plurality of data subsets, for providing each of the plurality of data subsets to one of the plurality of compression engines, and for transmitting the compressed data. The real-time wideband compressor is highly advantageous in, for example, space applications by programmable enabling performance of different techniques of codevector training as well as different techniques of VQ. Furthermore, after the compression process is started the compression process is performed autonomously without external communication.

    摘要翻译: 本发明涉及用于多维数据的实时宽带压缩器。 压缩机包括多个压缩引擎,用于同时压缩一组输入数据向量的多个数据子集,并使用SAMVQ或HSOCVQ数据压缩之一提供其压缩数据。 每个压缩引擎包括沿着频谱矢量码矢量训练器以及跨频谱带码矢量训练器。 压缩引擎可编程为可以在不改变硬件的情况下,沿着频谱矢量码矢量训练或跨频谱频带编码矢量训练与SAMVQ或HSOCVQ技术中的一种进行组合。 该压缩器还包括网络交换机,用于将该组输入数据向量划分成多个数据子集,用于将多个数据子集中的每一个提供给多个压缩引擎中的一个,并用于发送压缩数据。 实时宽带压缩器在例如空间应用中通过可编程实现不同技术的码向量训练以及不同的VQ技术是非常有利的。 此外,在压缩处理开始之后,压缩处理在没有外部通信的情况下自主地执行。

    Method of coding a continuous data flow using vector quantization
    7.
    发明申请
    Method of coding a continuous data flow using vector quantization 有权
    使用向量量化对连续数据流进行编码的方法

    公开(公告)号:US20090279805A1

    公开(公告)日:2009-11-12

    申请号:US12453426

    申请日:2009-05-11

    IPC分类号: G06K9/36

    CPC分类号: G06T9/008

    摘要: Methods and systems for compressing a continuous data flow for numerous applications where it is necessary to process large data sets such as hyper-spectral data cubes in real-time. A predetermined number of 2D focal plane frames in a boundary area of a previous regional data cube close to a current regional data cube are included in a training set used for codevector training for the current region. Therefore, no artificial boundary occurs between the two adjacent regions when codevectors trained in this way are used for codebook generation and encoding of the spectral vectors of the current regional data cube. This process substantially reduces image artifacts between adjacent regions. A remedy for the single bit error problem is also provided. Full redundancy of compressed data for a regional data cube is obtained by combining a previous regional data cube and the current regional data cube for codebook training. In order to obtain redundancy for the index map, the codebook is used to encode the current regional data cube as well as the previous regional data cube producing a baseline index map for the current regional data cube and a redundant index map for the previous regional data cube. Therefore, full redundancy for a regional data cube is provided allowing restoration of a regional data cube even if its codebook and/or index map are corrupted or lost due to single bit errors.

    摘要翻译: 用于压缩多个应用的​​连续数据流的方法和系统,其中需要实时处理诸如超光谱数据立方体之类的大数据集。 接近当前区域数据立方体的先前区域数据立方体的边界区域中的预定数量的2D焦平面帧被包括在用于当前区域的码矢量训练的训练集中。 因此,当以这种方式训练的代码矢量用于当前区域数据立方体的频谱矢量的码本生成和编码时,两个相邻区域之间不会发生人为边界。 该过程基本上减少相邻区域之间的图像伪像。 还提供了单位错误问题的补救措施。 通过组合先前的区域数据立方体和当前用于码本训练的区域数据立方体,获得区域数据立方体的压缩数据的完全冗余度。 为了获得索引图的冗余,码本用于对当前区域数据立方体以及以前的区域数据立方体进行编码,以生成当前区域数据立方体的基线索引图,以及用于先前区域数据的冗余索引图 立方体。 因此,提供区域数据立方体的完全冗余,允许恢复区域数据立方体,即使其码本和/或索引映射由于单个位错误而损坏或丢失。

    Method and system for compressing a continuous data flow in real-time using cluster successive approximation multi-stage vector quantization (SAMVQ)

    公开(公告)号:US07551785B2

    公开(公告)日:2009-06-23

    申请号:US10611897

    申请日:2003-07-03

    IPC分类号: G06K9/36 G06K9/00 H04B1/66

    CPC分类号: G06T9/008

    摘要: The present invention relates to a method and system for compressing a continuous data flow in real-time based on lossy compression. In real-time data compression, a series of multi-dimensional data subsets acquired in a given period of time are treated as a regional data cube for the purpose of dividing a continuous series of data subsets into a plurality of data cubes. In a first embodiment implementation of parallel processing using a plurality of compression engines is facilitated by separating a data cube into a plurality of clusters comprising similar spectral vectors. By separating the data cube into clusters of similar spectral vectors no artificial spatial boundaries are introduced substantially improving image quality. Furthermore, the spectral vectors within a cluster are more easily compressed due to their similarity. In a second embodiment a predetermined number of 2D focal plane frames in a boundary area of a previous regional data cube close to a current regional data cube are included in a training set used for codevector training for the current region. Therefore, no artificial boundary occurs between the two adjacent regions when codevectors trained in this way are used for codebook generation and encoding of the spectral vectors of the current regional data cube substantially reducing image artifacts between adjacent regions. A remedy for the single bit error problem is provided in a third embodiment. Full redundancy of compressed data for a regional data cube is obtained by combining the previous regional data cube and the current regional data cube for codebook training. In order to obtain redundancy for the index map, the codebook is used to encode the current regional data cube as well as the previous regional data cube producing a baseline index map for the current regional data cube and a redundant index map for the previous regional data cube. Therefore, full redundancy for a regional data cube is provided allowing restoration of a regional data cube if its codebook and/or index map are corrupted or lost due to single bit errors.

    System and method for encoding/decoding multidimensional data using successive approximation multi-stage vector quantization
    9.
    发明授权
    System and method for encoding/decoding multidimensional data using successive approximation multi-stage vector quantization 失效
    使用逐次逼近多级矢量量化对多维数据进行编码/解码的系统和方法

    公开(公告)号:US06701021B1

    公开(公告)日:2004-03-02

    申请号:US09717220

    申请日:2000-11-22

    IPC分类号: G06K9456

    CPC分类号: H04N19/94 G06T9/008

    摘要: The present method relates to a method for encoding image data using vector quantization. According to the invention, a small first codebook is determined. Each image vector of the image data is then encoded by determining a codevector within the first codebook that best approximates the image vector within the image data. A first index map is generated by replacing each image vector with an index indicative of the codevector's location within the first codebook. Then difference data are evaluated based on the original image data and the encoded image data. Each error vector of the difference data is then encoded using another small codebook. In another index map the error vectors are then replaced with an index indicative of the codevector's location within the other codebook. Evaluation of the error based on the difference data and the encoded difference data provides new difference data which is used to evaluate the fidelity of the approximation process performed for compression. The steps of encoding of the difference data are repeated until a control error of the difference data is smaller than a given threshold.

    摘要翻译: 本方法涉及使用矢量量化对图像数据进行编码的方法。 根据本发明,确定了小的第一码本。 然后通过确定最接近图像数据内的图像矢量的第一码本内的码矢来对图像数据的每个图像矢量进行编码。 通过用表示第一码本中的码矢量的位置的索引替换每个图像矢量来生成第一索引图。 然后基于原始图像数据和编码图像数据来评估差异数据。 然后使用另一个小码本对差数据的每个误差向量进行编码。 在另一个索引图中,然后用指示代码向量在另一码本内的位置的索引替换错误向量。 基于差分数据和编码的差分数据对误差的评估提供了用于评估对压缩执行的近似处理的保真度的新的差分数据。 重复差分数据的编码步骤,直到差分数据的控制误差小于给定的阈值。