Invention Application
US20160202346A1 Using An MM-Principle to Enforce a Sparsity Constraint on Fast Image Data Estimation From Large Image Data Sets 有权
使用MM原理来强制从大图像数据集快速图像数据估计的稀疏约束

Using An MM-Principle to Enforce a Sparsity Constraint on Fast Image Data Estimation From Large Image Data Sets
Abstract:
The mathematical majorize-minimize principle is applied in various ways to process the image data to provide a more reliable image from the backscatter data using a reduced amount of memory and processing resources. A processing device processes the data set by creating an estimated image value for each voxel in the image by iteratively deriving the estimated image value through application of a majorize-minimize principle to solve a maximum a posteriori (MAP) estimation problem associated with a mathematical model of image data from the data. A prior probability density function for the unknown reflection coefficients is used to apply an assumption that a majority of the reflection coefficients are small. The described prior probability density functions promote sparse solutions automatically estimated from the observed data.
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