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STAR/OPDB WPOP Report. Jaime Daniels Wayne Bresky Nov 3, 2005. Topics. Feature Tracking: An investigation of an Optical Flow Approach Implementation of Error Estimation (EE) Technique Other Activities Planned for FY06 GOES-N readiness MTSAT readiness MODIS Winds Upgrades.
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STAR/OPDB WPOP Report Jaime Daniels Wayne Bresky Nov 3, 2005
Topics • Feature Tracking: An investigation of an Optical Flow Approach • Implementation of Error Estimation (EE) Technique • Other Activities Planned for FY06 • GOES-N readiness • MTSAT readiness • MODIS Winds Upgrades
Feature Tracking: An investigation of an Optical Flow Approach • Motivation • Recommended by the Working Group on methods at the last two International Winds Workshops (IWW6, IWW&) for further investigation & development • Suggested goal: Compare performance against standard correlation techniques used • Presentation made at the last IWW7 • “Motion Vectors in Weather Radar Images” • M. Peura and H. Hohti (FMI) • Optical flow algorithm adopted for this problem
Feature Tracking: An investigation of an Optical Flow Approach • Optical Flow is a commonly used technique in the vast computer vision field • Numerous optical flow approaches/algorithms are documented in the literature • Barron, J., D. Fleet, and S. Beauchemin, 1994: Systems and Experiments: Performance of Optical Flow Techniques. International Journal of Computer Vision, 12:1, 43-77. • General Definition: Optical flow is an approximation of the local image motion based upon local spatio-temporal derivatives of image intensity in a sequence of images • Underlying Assumption: Local changes in image intensity are explained only by motion
Feature Tracking: An investigation of an Optical Flow Approach • Current status • Optical flow algorithm selected for testing • Lucas, B., and Kanade, 1981: An iterative registration technique with an application to stereo vision. Proc. Int. Joint Conf on Artificial Intelligence, Aug24-28, Vancouver, British Columbia, 674-679 • Software developed for above algorithm and integrated within winds vector calculation software used here at NESDIS • Running very controlled experiments using “simulated” imagery to validate/measure algorithm performance • Primarily using GOES-11 5-min imagery • Visible, WV, and LWIR imagery
Preliminary Results Figure 4. GOES-11 visible cloud-drift winds (not quality controlled) generated from 5-min imagery using the standard correlation matching (control) and optical flow (test) algorithms.
Preliminary Results Table 2. Comparison statistics between collocated GOES-11 raw water vapor winds (all levels) generated using correlation matching and optical flow tracking and rawinsondes at 00Z on August 3, 2005.
Preliminary Findings • Correlation-based tracking algorithm works very well when tracking motion of a field of small cumulus clouds; optical flow method struggles more in this situation • Optical flow algorithm seemed to perform quite well with WV imagery • However…., significant slow speed bias is being observed which needs to be addressed if this method is become a viable method of tracking • Actively being worked by Wayne
Implementation of Error Estimation (EE) Technique • Goal: Integrate EE software within operational winds software • Work has started on this integration effort • Coordination with Chris Redder and John LeMarshall • Chris has supplied us with the EE software • Wayne is currently integrating the software • Real-time generation of EE by end of next week planned
Other Activities Planned for FY06 • GOES-N Readiness • Obtained latest transmittance coefficient files • Very few software mods required • GOES-N science test participation • Assess impacts of expected improvements to calibration, navigation/registration • G-PSDI proposal submitted • MTSAT Readiness • CIMSS developed capability with OSD/GS funding • G-PSDI proposal submitted to integrate MTSAT capability within operational winds code • MODIS Winds Upgrades (FY06 P-PSDI Proposal approved) • Coordinate with CIMSS group to integrate planned upgrades • Parallax correction • Mixed Terra & Aqua winds processing • Validation of