Content-Aware Adaptive Compression of Satellite Imagery Using Artificial Vision

Abstract

This thesis aims to improve image throughput from satellite to Earth by using Artificial Vision to perform data compression before the downlink. Onboard Analysis for Selective Imagery Compression (OASIC) is a hybrid compression algorithm designed for oceanic imagery, incorporating both lossless and lossy compression methods to achieve a high compression ratio with minimal noise on vessels of interest. This is achieved by separating the vessels from the surrounding ocean and storing them with high fidelity, while compressing the remainder of the image with low fidelity. The performance of OASIC is examined on full resolution panchromatic satellite images and compared to both lossless and lossy JPEG2000 compressed images. In nearly all configurations tested, OASIC outperforms JPEG2000, achieving an average fifteen-fold improvement in compression ratios while maintaining a nearly lossless fidelity for the vessels within the OASIC compressed images. This content-sensitive compression algorithm can potentially enable the transmission of higher spatial resolution images, with more spectral bands, and at higher download speeds from space.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA589472

Entities

People

  • Jeffrey P. Wilcox

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Space

DTIC Thesaurus Topics

  • Artificial Satellites
  • Compressed Sensing
  • Computer Vision
  • Data Compression
  • Detection
  • Detectors
  • Feature Extraction
  • Image Compression
  • Image Processing
  • Information Science
  • Low Earth Orbits
  • Machine Learning
  • Naval Warfare
  • Pattern Recognition
  • Remote Sensing
  • Self Organizing Systems
  • Supervised Machine Learning

Readers

  • Computer Vision.
  • Image Processing and Computer Vision.

Technology Areas

  • Space
  • Space - Satellites