Weilin Hou

A simple underwater imaging model.

It is commonly known that underwater imaging is hindered by both absorption and scattering by particles of various origins. However, evidence also indicates that the turbulence in natural underwater environments can cause severe image-quality degradation. A model is presented to include the effects of both particle and turbulence on underwater optical imaging through optical transfer functions to help quantify the limiting factors under different circumstances. The model utilizes Kolmogorov-type index of refraction power spectra found in the ocean, along with field examples, to demonstrate that optical turbulence can limit imaging resolution by affecting high spatial frequencies. The effects of the path radiance are also discussed.

Optical turbulence on underwater image degradation in natural environments

It is a well-known fact that the major degradation source on electro-optical imaging underwater is from scattering by particles of various origins and sizes. Recent research indicates that, under certain conditions, the apparent degradation could also be caused by the variations of index of refraction associated with temperature and salinity microstructures in the ocean and lakes. The combined impact has been modeled previously through the simple underwater imaging model. The current study presents the first attempts in quantifying the level of image degradation due to optical turbulence in natural waters in terms of modulation transfer functions using measured turbulence dissipation rates. Image data collected from natural environments during the Skaneateles Optical Turbulence Exercise are presented. Accurate assessments of the turbulence conditions are critical to the model validation and were measured by two instruments to ensure consistency and accuracy. Optical properties of the water column in the field were also measured in coordination with temperature, conductivity, and depth. The results show that optical turbulence degrades the image quality as predicted and on a level comparable to that caused by the particle scattering just above the thermocline. Other contributing elements involving model closure, including temporal and spatial measurement scale differences among sensors and mitigation efforts, are discussed.

Comparison and validation of point spread models for imaging in natural waters

It is known that scattering by particulates within natural waters is the main cause of the blur in underwater images. Underwater images can be better restored or enhanced with knowledge of the point spread function (PSF) of the water. This will extend the performance range as well as the information retrieval from underwater electro-optical systems, which is critical in many civilian and military applications, including target and especially mine detection, search and rescue, and diver visibility. A better understanding of the physical process involved also helps to predict system performance and simulate it accurately on demand. The presented effort first reviews several PSF models, including the introduction of a semi-analytical PSF given optical properties of the medium, including scattering albedo, mean scattering angles and the optical range. The models under comparison include the empirical model of Duntley, a modified PSF model by Dolin et al, as well as the numerical integration of analytical forms from Wells, as a benchmark of theoretical results. For experimental results, in addition to that of Duntley, we validate the above models with measured point spread functions by applying field measured scattering properties with Monte Carlo simulations. Results from these comparisons suggest it is sufficient but necessary to have the three parameters listed above to model PSFs. The simplified approach introduced also provides adequate accuracy and flexibility for imaging applications, as shown by examples of restored underwater images.

Imagery-derived modulation transfer function and its applications for underwater imaging

The main challenge working with underwater imagery results from both rapid decay of signals due to absorption, which leads to poor signal to noise returns, and the blurring caused by strong scattering by the water itself and constituents within, especially particulates. The modulation transfer function (MTF) of an optical system gives the detailed and precise information regarding the system behavior. Underwater imageries can be better restored with the knowledge of the system MTF or the point spread function (PSF), the Fourier transformed equivalent, extending the performance range as well as the information retrieval from underwater electro-optical system. This is critical in many civilian and military applications, including target and especially mine detection, search and rescue, and diver visibility. This effort utilizes test imageries obtained by the Laser Underwater Camera Imaging Enhancer (LUCIE) from Defense Research and Development Canada (DRDC), during an April-May 2006 trial experiment in Panama City, Florida. Imaging of a standard resolution chart with various spatial frequencies were taken underwater in a controlled optical environment, at varying distances. In-water optical properties during the experiment were measured, which included the absorption and attenuation coefficients, particle size distribution, and volume scattering function. Resulting images were preprocessed to enhance signal to noise ratio by averaging multiple frames, and to remove uneven illumination at target plane. The MTF of the medium was then derived from measurement of above imageries, subtracting the effect of the camera system. PSFs converted from the measured MTF were then used to restore the blurred imageries by different deconvolution methods. The effects of polarization from source to receiver on resulting MTFs were examined and we demonstrate that matching polarizations do enhance system transfer functions. This approach also shows promise in deriving medium optical properties including absorption and attenuation.

Impacts of underwater turbulence on acoustical and optical signals and their linkage

Acoustical and optical signal transmission underwater is of vital interest for both civilian and military applications. The range and signal to noise during the transmission, as a function of system and water optical properties, in terms of absorption and scattering, determines the effectiveness of deployed electro-optical (EO) technology. The impacts from turbulence have been demonstrated to affect system performance comparable to those from particles by recent studies. This paper examines the impacts from underwater turbulence on both acoustic scattering and EO imaging degradation, and establishes a framework that can be used to correlate these. It is hypothesized here that underwater turbulence would influence the acoustic scattering cross section and the optical turbulence intensity coefficient in a similar manner. Data from a recent field campaign, Skaneateles Optical Turbulence Exercise (SOTEX, July, 2010) is used to examine the above relationship. Results presented here show strong correlation between the acoustic scattering cross-sections and the intensity coefficient related to the modulation transfer function of an EO imaging system. This significant finding will pave ways to utilize long range acoustical returns to predict EO system performance.

Assessing the Application of Cloud–Shadow Atmospheric Correction Algorithm on HICO

Several ocean color earth observation satellite sensors are presently collecting daily imagery, including the Hyperspectral Imager for the Coastal Ocean (HICO). HICO has been operating aboard the International Space Station since its installation on September 24, 2009. It provides high spatial resolution hyperspectral imagery optimized for the coastal ocean. Atmospheric correction, however, still remains a challenge for this sensor, particularly in optically complex coastal waters. In this paper, we assess the application of the cloud-shadow atmospheric correction approach on HICO data and validate the results with the in situ data. We also use multiple sets of cloud, shadow, and sunlit pixels to correct a single image multiple times and intercompare the results to assess variability in the retrieved reflectance spectra. Retrieved chlorophyll values from this intercomparison are similar and also agree well with the in situ chlorophyll measurements.

Quantification of optical turbulence in the ocean and its effects on beam propagation.

The influence of optically active turbulence on the propagation of laser beams is investigated in clear ocean water over a path length of 8.75 m. The measurement apparatus is described and the effects of optical turbulence on the laser beam are presented. The index of refraction structure constant is extracted from the beam deflection and the results are compared to independently made measures of the turbulence strength (Cn2) by a vertical microstructure profiler. Here we present values of Cn2 taken from aboard the R/V Walton Smith during the Bahamas optical turbulence exercise (BOTEX) in the Tongue of the Ocean between June 30 and July 12, 2011, spanning a range from 10-14 to 10-10  m-2/3. To the best of our knowledge, this is the first time such measurements are reported for the ocean.

Impacts of optical turbulence on underwater imaging

Optical signal transmission underwater is of vital interests to both civilian and military applications. The range and signal to noise during the transmission, as a function of system and water optical properties determines the effectiveness of EO technology. These applications include diver visibility, search and rescue, mine detection and identification, and optical communications. The impact of optical turbulence on underwater imaging has been postulated and observed by many researchers. However, no quantative studies have been done until recently, in terms of both the environmental conditions, and impacts on image quality as a function of range and spatial frequencies. Image data collected from field measurements during SOTEX (Skaneateles Optical Turbulence Exercise, July 22-31, 2010) using the Image Measurement Assembly for Subsurface Turbulence (IMAST) are presented. Optical properties of the water column in the field were measured using WETLabs ac-9 and Laser In Situ Scattering and Transmissometer (LISST, Sequoia Scientific), in coordination with physical properties including CTD (Seabird), dissipation rate of kinetic energy and heat, using both the Vector velocimeter and CT combo (Nortek and PME), and shear probe based Vertical Microstructure Profiler (VMP, Rockland). The strong stratification structure in the water column provides great opportunity to observe various dissipation strengths throughout the water column, which corresponds directly with image quality as shown. Initial results demonstrate general agreement between data collected and model prediction, while discrepancies between measurements and model suggest higher spatial and temporal observations are needed in the future.

Image feature detection and matching in underwater conditions

The main challenge in underwater imaging and image analysis is to overcome the effects of blurring due to the strong scattering of light by the water and its constituents. This blurring adds complexity to already challenging problems like object detection and localization. The current state-of-the-art approaches for object detection and localization normally involve two components: (a) a feature detector that extracts a set of feature points from an image, and (b) a feature matching algorithm that tries to match the feature points detected from a target image to a set of template features corresponding to the object of interest. A successful feature matching indicates that the target image also contains the object of interest. For underwater images, the target image is taken in underwater conditions while the template features are usually extracted from one or more training images that are taken out-of-water or in different underwater conditions. In addition, the objects in the target image and the training images may show different poses, including rotation, scaling, translation transformations, and perspective changes. In this paper we investigate the effects of various underwater point spread functions on the detection of image features using many different feature detectors, and how these functions affect the capability of these features when they are used for matching and object detection. This research provides insight to further develop robust feature detectors and matching algorithms that are suitable for detecting and localizing objects from underwater images.

Experimental study of a compressive line sensing imaging system in a turbulent environment

Turbulence poses challenges in many atmospheric and underwater surveillance applications. The compressive line sensing (CLS) active imaging scheme has been demonstrated in simulations and test tank experiments to be effective in scattering media such as turbid coastal water, fog, and mist. The CLS sensing model adopts the distributed compressive sensing theoretical framework that exploits both intrasignal sparsity and the highly correlated nature of adjacent areas in a natural scene. During sensing operation, the laser illuminates the spatial light modulator digital micromirror device to generate a series of one-dimensional binary sensing patterns from a codebook to encode the current target line segment. A single element detector photomultiplier tube acquires target reflections as the encoder output. The target can then be recovered using the encoder output and a predicted on-target codebook that reflects the environmental interference of original codebook entries. In this work, we investigated the effectiveness of the CLS imaging system in a turbulent environment. The development of a compact CLS prototype will be discussed, as will a series of experiments using various turbulence intensities at the Naval Research Labs Simulated Turbulence and Turbidity Environment. The experimental results showed that the time-averaged measurements improved both the signal-to-noise radio and the resolution of the reconstructed image in the extreme turbulence environment. The contributing factors for this intriguing and promising result will be discussed.