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Computationally efficient modeling of imagery using scaled, extracted principal components

机译:使用缩放的提取主成分进行图像的计算高效建模

摘要

A computationally efficient modeling system for imagery scales both the original image and corresponding principal component tiles in the same proportion to be able to extract scaled principal components. The system includes recovery of feature weights for the image model by extracting the weights from the reduced size principal component tiles. The use of the reduced size tiles to derive weights dramatically reduces computer overhead both in the generation of the files and in the generation of the weights, and is made possible by the fact that the weights from the scaled down tiles are nearly equal to the weights of the tiles associated with the full size image. The subject system thus reduces computation and the number of bits required to represent features by first scaling the image and then tiling the image in the same proportion. In one embodiment, the scaled down tiles are used as training exemplars used to generate the principal components.
机译:一种用于图像的高效计算建模系统,可以按相同比例缩放原始图像和相应的主成分图块,以便能够提取缩放后的主成分。该系统包括通过从尺寸减小的主成分块中提取权重来恢复图像模型的特征权重。使用减小尺寸的图块来获得权重可大大减少文件生成和权重生成中的计算机开销,并且由于缩小的图块的权重几乎等于权重这一事实而成为可能与全尺寸图片相关联的图块。因此,本主题系统通过首先缩放图像然后以相同比例平铺图像来减少表示特征所需的计算量和位数。在一个实施例中,按比例缩小的瓦片用作用于生成主分量的训练示例。

著录项

  • 公开/公告号US7113654B2

    专利类型

  • 公开/公告日2006-09-26

    原文格式PDF

  • 申请/专利权人 LEONARD E. RUSSO;

    申请/专利号US20020334816

  • 发明设计人 LEONARD E. RUSSO;

    申请日2002-12-31

  • 分类号G06K9/32;

  • 国家 US

  • 入库时间 2022-08-21 21:43:11

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