Creating Orthographically Rectified Satellite Multi-Spectral Imagery with High Resolution Digital Elevation Model from LiDAR: A Tutorial

Abstract

Orthoimages are used to produce image-map products for navigation and planning, and serve as source data for advanced research, development, testing, and evaluation of feature extraction methods. This tutorial describes procedures for making orthoimages from Light Detection and Ranging (LiDAR) Digital Elevation Models (DEM) and from commercial satellite Multi-Spectral Imagery (MSI) in the National Imagery Transmission Format (NITF) with Rational Polynomial Coefficients (RPC). Orthoimages rectify digital imagery to remove geometric distortions caused by the varying elevations of the exposed terrain features, and by exterior and interior orientations of the sensor. When orthoimages are combined, the resulting mosaic covers a wider area and contains less visible seams, which makes the map easier to understand. RPC replace the actual sensor model while processing the original MSI. This generic replacement sensor model is provided with the distributed imagery to simplify the process of removing the geometric distortions so image processing software can create orthoimages without using the actual sensor model, which is often not provided. The DEM and MSI also become better registered together after producing the orthoimage by using the RPC. This assists feature extraction and segmentation when the DEM is added as extra data bands to the MSI.

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Document Details

Document Type
Technical Report
Publication Date
Aug 15, 2014
Accession Number
ADA610394

Entities

People

  • Roger O. Brown

Organizations

  • United States Army Corps of Engineers

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Artificial Satellites
  • Coordinate Systems
  • Detection
  • Detectors
  • Digital Elevation Models
  • Feature Extraction
  • Grids
  • High Resolution
  • Image Processing
  • Lidar
  • Mathematics
  • Models
  • Navigation
  • Orientation (Direction)
  • Remote Sensing
  • Satellite Imaging
  • World Geodetic System

Readers

  • Computer Vision.

Technology Areas

  • AI & ML
  • Space