Accession Number:

ADA621621

Title:

Bio-Inspired Sampling and Reconstruction Framework for Scientific Visualization

Descriptive Note:

Final rept. 1 Jun 2012-31 Jul 2015

Corporate Author:

FLORIDA UNIV GAINESVILLE

Personal Author(s):

• Entezari, Alireza

Report Date:

2015-09-17

Pagination or Media Count:

10.0

Abstract:

This project investigated sampling theoretic issues that arise in visualization of 3-D e.g., in simulation or biomedical datasets. As sampling and reconstruction are key elements in the visualization pipeline, their mathematical modeling and analysis are foundational to reliability of the resulting visualizations. An important achievement of this investigation is establishing the superiority of optimal lattices for reconstruction of scattered data. These lattices are observed in nature as crystallographic structures e.g., body centered cubic and face centered cubic lattices, as well as biological vision systems e.g., hexagonal lattice. While the sampling theoretic advantages of optimal lattices have been established, practical tools e.g., filtering, interpolation, wavelet analysis, signal reconstruction, regularization methods for exploiting these advantages have been unavailable to practitioners.

Descriptors:

• *BIOMEDICAL INFORMATION SYSTEMS
• *IMAGE PROCESSING
• *LATTICE DYNAMICS
• *RELATIONAL DATA BASES
• *VISUAL AIDS
• BIOMEDICINE
• CLUSTERING
• COMPUTERIZED SIMULATION
• DATA MINING
• ERRORS
• FEATURE EXTRACTION
• IMAGE RECONSTRUCTION
• INTERPOLATION
• LINEARITY
• MATHEMATICAL FILTERS
• MATHEMATICAL MODELS
• MONTE CARLO METHOD
• OPTIMIZATION
• PROBABILITY DENSITY FUNCTIONS
• RELIABILITY
• SOFTWARE TOOLS
• THREE DIMENSIONAL
• UNCERTAINTY

Subject Categories:

• Information Science
• Medicine and Medical Research
• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE