METHOD OF PROCESSING SPATIAL-TEMPORAL DATA PROCESSING
In one embodiment, the invention includes a method of formulating a parametric model from spatial-temporal data including fitting model parameters calculated from spatial-temporal data to at least one displacement model and calculating new spatial temporal data based on the model. In another embodiment, the invention includes a method of processing spatial-temporal data including filtering the spatial temporal data and assessing data quality based on data quality metrics.
1 . A method of processing spatial-temporal data comprising:
filtering the spatial-temporal data; and
assessing data quality based on a data quality metric.
2 . The method of claim 1 wherein the step of filtering the spatial-temporal data includes temporal filtering.
3 . The method of claim 2 wherein the spatial-temporal data is filtered with at least one filter selected from the group consisting of: Finite Impulse Response Filter and Infinite Impulse Response Filter.
4 . The method of claim 3 wherein the Finite Impulse Response Filter includes space-time filtering.
5 . The method of claim 4 wherein the space-time filtering is performed with at least one method selected from the group consisting of: 3-D kernel convolution and 3-D Fourier transform multiplication.
6 . The method of claim 1 wherein the step of filtering the spatial-temporal data includes a Kalman filter.
7 . The method of claim 1 wherein the step of assessing data quality includes at least one method selected from the group consisting of: sample elimination, sample interpolation, sample weighting, sample thresholding, and a combination of sample weighting and sample thresholding.
8 . The method of claim 7 wherein the step of assessing data quality includes assessing data quality based on at least one data quality metric selected from the group consisting of: peak correlation, spatial and temporal variation of displacement, and spatial and temporal variations of correlation magnitude.
9 . The method of claim 1 wherein the step of assessing data quality includes assessing data quality based on at least one data quality metric selected from the group consisting of: peak correlation, spatial and temporal variation of displacement, and spatial and temporal variations of correlation magnitude.
10 . The method of claim 1 wherein the spatial-temporal data is a real-time datastream.
11 . The method of claim 1 wherein the spatial-temporal data is a stored datastream.
12 . The method of claim 1 wherein the spatial-temporal data includes acoustic frames.
13 . The method of claim 1 wherein the spatial-temporal data includes scan converted images.
14 . A method of formulating a parametric model from spatial-temporal data comprising:
fitting model parameters calculated from spatial-temporal data to at least one displacement model; and
calculating new spatial temporal data based on the model.
15 . The method of claim 14 , further comprising the step of assessing data quality based on data quality metrics.
16 . The method of claim 14 wherein the step of evaluating data quality includes at least one method selected from the group consisting of: sample elimination, sample interpolation, sample weighting, sample thresholding, or a combination of sample weighting and sample thresholding.
17 . The method of claim 14 wherein the spatial-temporal data is a real-time datastream.
18 . The method of claim 14 wherein the spatial-temporal data is a stored datastream.
19 . The method of claim 14 wherein the spatial-temporal data includes acoustic frames.
20 . The method of claim 14 wherein the spatial-temporal data includes scan converted images.