Empirical wavelets, deep learning for image restoration. Application to atmospheric turbulence mitigation

Abstract

The proposed work aims at exploring the development of data-driven image processing techniques for the purpose of image restoration and particularly from a sequence of frames acquired through atmospheric turbulence. He will focus on two main approaches: the use of empirical wavelets and deep learning tools.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 21, 2022
Source ID
FA95502110275XX0

Entities

People

  • Jérôme Gilles

Organizations

  • Air Force Office of Scientific Research
  • Salk Institute for Biological Studies
  • United States Air Force

Tags

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Neural Network Machine Learning.
  • Wetland-Land-Environmental Management.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks