Dynamic Range Compression Deconvolution for Enhancement of Automatic Target Recognition System Performance

Abstract

A generic nonlinear dynamic range compression deconvolver (DRCD) is proposed. We have performed the dynamic range compression deconvolution using three forms of nonlinearities: (1) digital implementation- A-law/ -law, (2) hybrid digital-optical implementation- two-beam coupling photorefractive holography, and (3) all optical implementation- MEMS deformable mirrors. The performance of image restoration improves as the saturation nonlinearity increases. The DRCD could be used as a preprocessor for enhancing Automatic Target Recognition (ATR) system performance. In imaging through atmosphere, factors such as rain, snow, haze, pollution, etc. affect the received information from a target; therefore the need for correcting these captured images before an ATR system is required. The DRCD outperforms well-established image restoration filters such as the inverse and the Wiener filters.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 03, 2008
Accession Number
ADA482319

Entities

People

  • Bahareh Haji-saeed
  • Charles L. Woods
  • Jed Khoury
  • John Kierstead
  • William Goodhue

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Sensors

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Atmospheric Motion
  • Communication Systems
  • Compression
  • Computer Programs
  • Deformable Mirrors
  • Detection
  • Dynamic Range
  • Image Processing
  • Image Restoration
  • Microelectromechanical Systems
  • Optical Correlators
  • Optical Modulators
  • Recognition
  • Signal Processing
  • Target Recognition
  • Wave Propagation

Fields of Study

  • Engineering
  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.
  • Optical Physics and Photonics.