Automated Underwater Image Restoration and Retrieval of Related Optical Properties
Abstract
This study is aimed at establishing a framework to restore underwater imagery to the best possible level, working with both simulated and field-measured data. Using this framework, the traditional image restoration approach is extended by incorporating underwater optical properties into the system response function, specifically the point spread function (PSF) in the spatial domain and the modulation transfer function (MTF) in the frequency domain. Due to the intensity variations involved in underwater sensing, denoising is carefully carried out by wavelet decompositions. This process is necessary for exploring different effects of restoration constraints, and especially their response to the underwater environment, where the effects of scattering can be easily treated as either signal or noise. The images are then restored using measured or modeled PSFs. An objective image quality metric, tuned with environmental optical properties, is designed to gauge the effectiveness of the restoration, and serves to check the optimization approach. This metric utilizes previous wavelet decompositions to constrain the sharpness metric based on gray-scale slopes at the edge, weighted by the ratio of the power of high frequency components of the image to the total power of the image. Modeled PSFs, based on Wells' small-angle approximations, are compared to those derived from Monte Carlo simulation using measured scattering properties. Initial results are presented, including the estimation of water optical properties from the imagery-derived MTFs, and optimization outputs applying the automated restoration framework.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2007
- Accession Number
- ADA474300
Entities
People
- Alan Dean Weidemann
- Deric J Gray
- Georges R. Fournier
- J. L. Forand
- Weilin W. Hou
Organizations
- United States Naval Research Laboratory