Evaluation of the Navy's Semi-Automated Mesoscale Analysis System (SMAS)

Abstract

The feasibility of automated analysis of satellite imagery for positions of mesoscale ocean features has been demonstrated. Weaknesses in Version 1.0 have been identified and now form the rational for further research. Specifically, improvements have been initiated in the area of segmentation, where a new segmenter utilizing both edge and region information is under development. This first evaluation has also revealed that the feature labeling algorithm is too closely tied to the initial guess. Improvements in this area are also underway. A new approach to feature labeling using genetic algorithms is also under investigation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1990
Accession Number
ADA237978

Entities

People

  • Ronald J. Holyer
  • Sarah H. Peckinpaugh

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Cloud Cover
  • Computer Vision
  • Detection
  • Detectors
  • Expert Systems
  • Genetic Algorithms
  • Gulf Stream
  • Image Processing
  • Image Segmentation
  • Oceanography
  • Oceans
  • Remote Sensing
  • Satellite Imaging
  • Sea Surface Temperature

Readers

  • Computer Vision.
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology
  • Space