Computational Expenditure Reduction in Pseudo-Gradient Image Parameter Estimation

机译：伪梯度图像参数估计中的计算支出减少

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摘要

An approach enabling to reduce computational expenses at pseudogradient estimation of image parameters based on control of goal function local sample volume is proposed. Local sample volume variation during the process of parameter estimation occurs automatically in correspondence with a preassigned criterion, for instance, sample correlation coefficient. It is shown that for the problems of image mutual spatial deformation parameter estimation, computational expenses can be reduced several times as many.

机译：提出了一种基于目标函数局部样本量控制的方法，能够减少图像参数伪梯度估计时的计算量。参数估计过程中的局部样本量变化会根据预先指定的标准（例如样本相关系数）自动发生。结果表明，针对图像相互空间变形参数估计的问题，可以将计算费用减少几倍。

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《International Conference on Computational Science - ICCA 2003 Pt.2 Jun 2-4, 2003 Melbourne, Australia and St. Petersburg, Russia》|2003年|p.456-462|共7页
会议地点 Melbourne(AU) St. Petersburg(RU);Melbourne(AU) St. Petersburg(RU)
作者
Alexandr Tashlinskii;
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作者单位

Ulyanovsk State Technical University, 32 Severnyi Venetz Str., 432027 Ulyanovsk Russia;

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原文格式 PDF
正文语种 eng
中图分类自动化技术、计算机技术;
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Computational Expenditure Reduction in Pseudo-Gradient Image Parameter Estimation

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