Objective Feature Identification and Tracking: A Review

Abstract

Remote sensing of the oceans via satellites is providing useful data that can be used for realtime input into and verification of the numerical ocean models. To make an optimum use of these data, efficient methods are being developed to handle vast amounts of data and provide their quick analyses and summaries in the form of mesoscale features. Identification, isolation and tracking of mesoscale features plays an important role in numerical ocean modeling. Of late, there has been considerable interest in designing algorithms to automatically detect such oceanographic features as temperature fronts and eddies. This report provides a literature review of recent approaches and efforts on objective feature identification (OFI) as it pertains to oceanographic applications. Most of the OFI work in oceanography has been done on characterizing the Gulf Stream (GS); and since the GS incorporates all the mesoscale feature complexities that one may desire to resolve, the literature reviewed here pertains to this feature entirely. It is felt that the work cited is quite representative and is applicable to other geographical features of interest.

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Document Details

Document Type
Technical Report
Publication Date
Sep 15, 1994
Accession Number
ADA284955

Entities

People

  • Harsh Anand
  • Ranjit M. Passi

Organizations

  • Mississippi State University

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Change Detection
  • Computer Vision
  • Detection
  • Detectors
  • Expert Systems
  • Feature Extraction
  • Grids
  • Gulf Stream
  • Identification
  • Image Processing
  • Oceans
  • Pattern Recognition
  • Statistical Algorithms
  • Three Dimensional
  • Two Dimensional

Readers

  • Computer Vision.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design

Technology Areas

  • Space
  • Space - Space Objects