Invention Grant
- Patent Title: Using an MM-principle to enforce a sparsity constraint on fast image data estimation from large image data sets
-
Application No.: US14305934Application Date: 2014-06-16
-
Publication No.: US09864046B2Publication Date: 2018-01-09
- Inventor: John M. M. Anderson , Mandoye Ndoye , Oludotun Ode , Henry C. Ogworonjo
- Applicant: Howard University
- Applicant Address: US DC Washington
- Assignee: Howard University
- Current Assignee: Howard University
- Current Assignee Address: US DC Washington
- Agency: Fitch Even Tabin & Flannery LLP
- Main IPC: G01S7/292
- IPC: G01S7/292 ; G01S13/88 ; G01S13/02 ; G01S13/89 ; G06K9/62 ; G06K9/00

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.
Public/Granted literature
Information query