Dr. Weilin "Will" Hou Profile

Dr. Weilin "Will" Hou

Oceanographer at US Naval Research Lab

SPIE Involvement:

Fellow status | Conference Chair | Journal Editorial Board Member | Author | Editor | Instructor

Area of Expertise:

ocean optics , underwater imaging , turbulence , remote sensing , numerical simulation , unmanned vehicle

Websites:

Company Website

Profile Summary

Weilin "Will" Hou is an oceanographer at the U. S. Naval Research Laboratory, and manages the Hydro Optics Sensors and Systems Section. He received his PhD from the College of Marine Science, University of South Florida in 1997. His research interests covers several areas in ocean sensing with optics techniques, with recent interests focusing on ocean turbulence, temperature and related sensor and techniques. Other areas of interests include ocean optics, underwater imaging, remote sensing especially lidar, numerical simulation, data management, instrumentation and platforms such as unmanned vehicles. He developed and chairs the annual SPIE Ocean Sensing and Monitoring conference since 2008, and teaches a short course on the related topics. He is the editor of 8 Proc. SPIE Vols, and author of the book "Ocean Sensing and Monitoring: Optics and Other Methods". He serves as an associate editor for the Journal of Applied Remote Sensing (JARS).

Book: Ocean Sensing and Monitoring: Optics and other Methods (2013)
https://www.scribd.com/document/366231399/Ocean-Sensing-and-Monitoring-Optics-and-Other-Methods

Job opening, research and employment opportunities:

1) Active Ocean Layer Sensing with Lidar

http://nrc58.nas.edu/RAPLab10/Opportunity/Opportunity.aspx?LabCode=64&ROPCD=641701&RONum=B7778

2) EO Imaging Applications in Oceanic Environments

http://nrc58.nas.edu/RAPLab10/Opportunity/Opportunity.aspx?LabCode=64&ROPCD=641701&RONum=B6900

Publications (53)

PROCEEDINGS ARTICLE | September 29, 2017

Characterization of underwater optical turbulence on the example of the Rayleigh-Benard water tank

Proc. SPIE. 10425, Optics in Atmospheric Propagation and Adaptive Systems XX

KEYWORDS: Refractive index, Light emitting diodes, Scattering, Water, Laser scattering, Wave propagation, Turbulence, Motion models, Optical turbulence, Motion measurement

SPIE Journal Paper | August 17, 2017

Special Section Guest Editorial: Recent Advances in Geophysical Sensing of the Ocean: Remote and In Situ Methods

Hou, Weilin , Arnone, Robert

JARS Vol. 11 Issue 03

KEYWORDS: Remote sensing, In situ remote sensing, Sensors, Atmospheric modeling, Signal attenuation, Satellites, Water, Hyperspectral imaging, Unmanned aerial vehicles, Biosensing

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SPIE Conference Volume | June 20, 2017

Ocean Sensing and Monitoring IX

PROCEEDINGS ARTICLE | June 7, 2017

Beam wander due to optical turbulence in water (Conference Presentation)

Proc. SPIE. 10186, Ocean Sensing and Monitoring IX

KEYWORDS: Water, Free space, Laser beam propagation, Ocean optics, Refraction, Optical communications, Optical simulations, Free space optics, Optical turbulence, Environmental sensing

PROCEEDINGS ARTICLE | June 7, 2017

Assessment of lidar remote sensing capability of Raman water temperature from laboratory and field experiments (Conference Presentation)

Proc. SPIE. 10186, Ocean Sensing and Monitoring IX

KEYWORDS: Polarization, LIDAR, Remote sensing, Laser applications, Raman spectroscopy, Turbulence, Profiling, Raman scattering, Photosynthesis, Climatology

Lidar remote sensing based on visible wavelength is one of the only way to penetrate the water surface and to obtain range resolved information of the ocean surface mixed layer at the synoptic scale. Accurate measurement of the mixed layer properties is important for ocean weather forecast and to assist the optimal deployment of military assets. Turbulence within the mixed layer also plays an important role in climate variability as it also influences ocean heat storage and algae photosynthesis (Sverdrup 1953, Behrenfeld 2010). As of today, mixed layer depth changes are represented in the models through various parameterizations constrained mostly by surface properties like wind speed, surface salinity and sea surface temperature. However, cooling by wind and rain can create strong gradients (0.5C) of temperature between the submillimeter surface layer and the subsurface layer (Soloviev and Lukas, 1997) which will manifest itself as a low temperature bias in the observations. Temperature and salinity profiles are typically used to characterize the mixed layer variability (de Boyer Montégut et al. 2004) and are both key components of turbulence characterization (Hou 2009). Recently, several research groups have been investigating ocean temperature profiling with laser remote sensing based either on Brillouin (Fry 2012, Rudolf and Walther 2014) or Raman scattering (Artlett and Pask 2015, Lednev et al. 2016). It is the continuity of promising research that started decades ago (Leonard et al. 1979, Guagliardo and Dufilho 1980, Hirschberg et al. 1984) and can benefit from the current state of laser and detector technology. One aspect of this research that has not been overlooked (Artlett and Pask 2012) but has yet to be revisited is the impact of temperature on vibrational Raman polarization (Chang and Young, 1972). The TURBulence Ocean Lidar is an experimental system, aimed at characterizing underwater turbulence by examining various Stokes parameters. Its multispectral capability in both emission (based on an optical parametric oscillator) and detection (optical filters) provide flexibility to measure the polarization signature of both elastic and inelastic scattering. We will present the characteristics of TURBOL and several results from our laboratory and field experiments with an emphasis on temperature profiling capabilities based on vibrational Raman polarization. We will also present other directions of research related to this activity.

PROCEEDINGS ARTICLE | May 22, 2017

The development of an underwater pulsed compressive line sensing imaging system

Proc. SPIE. 10186, Ocean Sensing and Monitoring IX

KEYWORDS: Visualization, Imaging systems, LIDAR, Image segmentation, Semiconductor lasers, Spatial light modulators, Turbulence, Sensing systems, Digital micromirror devices, Underwater imaging, Environmental sensing, Prototyping, Visual compression, Compressed sensing

PROCEEDINGS ARTICLE | May 22, 2017

The impact of optical turbulence on particle image velocimetry

Proc. SPIE. 10186, Ocean Sensing and Monitoring IX

KEYWORDS: Stars, Particles, CCD cameras, Refraction, Turbulence, CMOS cameras, Velocity measurements, Optical turbulence, Particle image velocimetry, Liquids

SPIE Journal Paper | May 3, 2017

Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

Ouyang, Bing , Hou, Weilin , Caimi, Frank , Dalgleish, Fraser , Vuorenkoski, Anni , Gong, Cuiling

JARS Vol. 11 Issue 03

KEYWORDS: Image quality, Digital image correlation, Compressed sensing, Imaging systems, Chromium, Backscatter, Image compression, Image restoration, Sensing systems, Unmanned aerial vehicles

SPIE Conference Volume | June 15, 2016

Ocean Sensing and Monitoring VIII

PROCEEDINGS ARTICLE | May 17, 2016

Measurements of optical underwater turbulence under controlled conditions

Proc. SPIE. 9827, Ocean Sensing and Monitoring VIII

KEYWORDS: Light emitting diodes, Phase modulation, Wavefront sensors, Ocean optics, Wave propagation, Turbulence, Modulation transfer functions, Geometrical optics, Atmospheric propagation, Atmospheric propagation, Beam propagation method

PROCEEDINGS ARTICLE | May 17, 2016

Velocity fields and optical turbulence near the boundary in a strongly convective laboratory flow

Proc. SPIE. 9827, Ocean Sensing and Monitoring VIII

KEYWORDS: Computational fluid dynamics, Tumor growth modeling, Data modeling, Particles, Computer simulations, Refraction, Turbulence, Optical turbulence, Radium, Temperature metrology

PROCEEDINGS ARTICLE | May 17, 2016

Experimental study of a DMD based compressive line sensing imaging system in the turbulence environment

Proc. SPIE. 9827, Ocean Sensing and Monitoring VIII

KEYWORDS: Imaging systems, Receivers, Data acquisition, Image quality, Turbulence, Sensing systems, Digital micromirror devices, Digital micromirror devices, Optical turbulence, Environmental sensing, Prototyping

PROCEEDINGS ARTICLE | May 12, 2016

A fiber-optic water flow sensor based on laser-heated silicon Fabry-Pérot cavity

Proc. SPIE. 9852, Fiber Optic Sensors and Applications XIII

KEYWORDS: Optical fibers, Fiber optics, Interferometers, Sensors, Silicon, Numerical simulations, Single mode fibers, Fiber optics sensors, Semiconductor lasers, Finite element methods

PROCEEDINGS ARTICLE | March 15, 2016

Experimental study of a DMD based compressive line sensing imaging system in the turbulence environment

Proc. SPIE. 9761, Emerging Digital Micromirror Device Based Systems and Applications VIII

KEYWORDS: Compressive imaging, Imaging systems, Scattering, LIDAR, Sensors, Receivers, Turbulence, Sensing systems, Digital micromirror devices, Optical turbulence, Electro optical imaging, Environmental sensing, Prototyping, Compressed sensing

SPIE Conference Volume | June 2, 2015

Ocean Sensing and Monitoring VII

PROCEEDINGS ARTICLE | May 19, 2015

A miniature fiber-optic sensor for high-resolution and high-speed temperature sensing in ocean environment

Proc. SPIE. 9459, Ocean Sensing and Monitoring VII

KEYWORDS: Thermal optics, Sensors, Silicon, Fiber optics sensors, Ocean optics, Head, Turbulence, Thermal effects, Environmental sensing, Temperature metrology

PROCEEDINGS ARTICLE | May 19, 2015

Ocean and polarization observations from active remote sensing: atmospheric and ocean science applications

Proc. SPIE. 9459, Ocean Sensing and Monitoring VII

KEYWORDS: LIDAR, Aerosols, Calibration, Water, Clouds, Ocean optics, Analytical research, Atmospheric particles, Atmospheric optics, Liquids

In the past few years, we have demonstrated how the surface return measured by the active instruments onboard CloudSat and CALIPSO could be used to retrieve the optical depth and backscatter phase function (lidar ratio) of aerosols and ice clouds. This methodology lead to the development of a data fusion product publicly available at the ICARE archive center using the Synergized Optical Depth of Aerosols and Ice Clouds (SODA & ICE) algorithm¹. This algorithm, also allowing to derive ocean surface wind speed, has been extended to include dense cloud surface return to analyze aerosol and cloud properties above such clouds. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: • A new characterization of the lidar ratio of cirrus clouds² • The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA³) • The analysis of the lidar ratio of sea-spray aerosols⁴, and of Aerosol multilayer lidar ratio and extinction⁵ • A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles⁶ In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained. This low level data fusion of CALIPSO and CloudSat ocean surface echoes has been used by several researchers to explore different research paths. Among them, we can cite: A new characterization of the lidar ratio of cirrus clouds² The analysis of the precipitable water and development of a new Millimeter-Wave Propagation Model for the W-Band observations (EMPIRIMA³) The analysis of the lidar ratio of sea-spray aerosols⁴, and of Aerosol multilayer lidar ratio and extinction⁵ A contribution to the retrieval of the subsurface particulate backscatter coefficients of phytoplankton particles⁶ In this paper, we present the main features of SODA & ICE, summarizing some of the results obtained.

PROCEEDINGS ARTICLE | May 19, 2015

A controlled laboratory environment to study EO signal degradation due to underwater turbulence

Proc. SPIE. 9459, Ocean Sensing and Monitoring VII

KEYWORDS: Data modeling, Sensors, Numerical simulations, Adaptive optics, Optical testing, Ocean optics, Refraction, Turbulence, Optical turbulence, Temperature metrology

PROCEEDINGS ARTICLE | May 19, 2015

Distributed compressive sensing vs. dynamic compressive sensing: improving the compressive line sensing imaging system through their integration

Proc. SPIE. 9459, Ocean Sensing and Monitoring VII

KEYWORDS: Image compression, Backscatter, Imaging systems, Scattering, Signal attenuation, Computer programming, Image quality, Sensing systems, Prototyping, Compressed sensing

PROCEEDINGS ARTICLE | May 14, 2015

Near-infrared compressive line sensing imaging system using individually addressable laser diode array

Proc. SPIE. 9484, Compressive Sensing IV

KEYWORDS: Image compression, Imaging systems, Sensors, Calibration, Receivers, Semiconductor lasers, Spatial light modulators, Digital micromirror devices, Prototyping, Fiber optic illuminators

PROCEEDINGS ARTICLE | May 13, 2015

Fiber optic anemometer based on silicon Fabry-Pérot interferometer

Proc. SPIE. 9480, Fiber Optic Sensors and Applications XII

KEYWORDS: Fiber optics, Fiber Bragg gratings, Interferometers, Sensors, Silicon, Fiber lasers, Fiber optics sensors, Semiconductor lasers, Silicon films, Infrared radiation

PROCEEDINGS ARTICLE | March 10, 2015

Wavefront sensing and analysis for underwater laser propagation

Proc. SPIE. 9335, Adaptive Optics and Wavefront Control for Biological Systems

KEYWORDS: Point spread functions, Fourier transforms, Wavefront sensors, Wavefronts, Laser beam propagation, Adaptive optics, Turbulence, Deconvolution, Analytical research, Light wave propagation

PROCEEDINGS ARTICLE | October 21, 2014

Correction methods for underwater turbulence degraded imaging

Proc. SPIE. 9242, Remote Sensing of Clouds and the Atmosphere XIX; and Optics in Atmospheric Propagation and Adaptive Systems XVII

KEYWORDS: Speckle, Image processing, Remote sensing, Image restoration, Adaptive optics, Image quality, Turbulence, Reconstruction algorithms, Underwater imaging, Atmospheric propagation

SPIE Conference Volume | June 13, 2014

Ocean Sensing and Monitoring VI

PROCEEDINGS ARTICLE | June 4, 2014

Adaptive optics correction of a laser beam propagating underwater

Proc. SPIE. 9083, Micro- and Nanotechnology Sensors, Systems, and Applications VI

KEYWORDS: Point spread functions, Sensors, Wavefront sensors, Wavefronts, Laser beam propagation, Adaptive optics, Turbulence, Analytical research, Optical calibration, Light wave propagation

PROCEEDINGS ARTICLE | May 23, 2014

Overview of a hybrid underwater camera system

Proc. SPIE. 9111, Ocean Sensing and Monitoring VI

KEYWORDS: Imaging systems, Cameras, Sensors, Signal attenuation, Control systems, Navigation systems, Image enhancement, System integration, Pulsed laser operation, Visibility

PROCEEDINGS ARTICLE | May 23, 2014

Experimental studies of the compressive line sensing underwater serial imaging system

Proc. SPIE. 9111, Ocean Sensing and Monitoring VI

KEYWORDS: Image compression, Imaging systems, Scattering, Image restoration, Computer programming, Spatial light modulators, Image quality, Sensing systems, Digital micromirror devices, Prototyping

PROCEEDINGS ARTICLE | May 23, 2014

The impact of turbulent fluctuations on light propagation in a controlled environment

Proc. SPIE. 9111, Ocean Sensing and Monitoring VI

KEYWORDS: Data modeling, Water, Numerical simulations, Optical testing, Ocean optics, Refraction, Turbulence, Integrated optics, Geometrical optics, Optical turbulence

SPIE Journal Paper | May 21, 2014

Special Section Guest Editorial: Ocean Optics

Hou, Weilin

OE Vol. 53 Issue 05

KEYWORDS: Ocean optics, LIDAR, Sensors, Atmospheric modeling, Monte Carlo methods, Signal detection, Water, Analytical research, Scattering, Absorption

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SPIE Press Author | August 8, 2013

Ocean Sensing and Monitoring: Optics and Other Methods

Hou, Weilin

SPIE Conference Volume | June 10, 2013

Ocean Sensing and Monitoring V

PROCEEDINGS ARTICLE | June 3, 2013

Measurements of turbulent dissipation during the Bahamas Optical Turbulence Experiment

Proc. SPIE. 8724, Ocean Sensing and Monitoring V

KEYWORDS: Optical properties, Error analysis, Tongue, Ocean optics, Turbulence, Velocity measurements, Intelligence systems, Optical turbulence, Temperature metrology, Tin

PROCEEDINGS ARTICLE | June 3, 2013

In situ laser sensing of mixed layer turbulence

Proc. SPIE. 8724, Ocean Sensing and Monitoring V

KEYWORDS: Backscatter, LIDAR, Sensors, Water, Laser scattering, High speed cameras, Turbulence, Profiling, Optical turbulence, Temperature metrology

This paper will discuss and compare some recent oceanic test results from the Bahamas Optical Turbulence Exercise (BOTEX) cruise, where vertical profiling was conducted with both time-resolved laser backscatter measurements being acquired via a subsurface light detection and ranging (lidar) profiling instrument, and laser beam forward deflection measurements were acquired from a matrix of continuous wave (cw) laser beams (i.e. structured lighting) being imaged in the forward direction with a high speed camera over a one-way path, with both transmitter and camera firmly fixed on a rigid frame. From the latter, it was observed that when within a natural turbulent layer, the laser beams were being deflected from their still water location at the image plane, which was 8.8 meters distance from the laser dot matrix transmitter. As well as suggesting that the turbulent structures being encountered were predominately larger than the beam diameter, the magnitude of the deflection has been confirmed to correlate with the temperature dissipation rate. The profiling lidar measurements which were conducted in similar conditions, also used a narrow collimated laser beam in order to resolve small-scale spatial structure, but with the added attribute that sub-nanosecond short pulse temporal profile could potentially resolve small-scale vertical structure. In the clear waters of the Tongue of the Ocean in the Bahamas, it was hypothesized that the backscatter anomalies due to the effect of refractive index discontinuities (i.e. mixed layer turbulence) would be observable. The processed lidar data presented herein indicates that higher backscatter levels were observed in the regions of the water column which corresponded to higher turbulent mixing which occurs at the first and second themoclines. At the same test stations that the laser beam matrix and lidar measurements were conducted, turbulence measurements were made with two non-optical instruments, the Vertical Microstructure Profiler (VMP) and a 3D acoustical Doppler velocimeter with fast conductivity and temperature probes. The turbulence kinetic energy dissipation rate and the temperature dissipation rates were calculated from both these setups in order to characterize the physical environments and corroborate with the laser measurements. To further investigate the utility of elastic lidar in detecting small-scale turbulent structures, controlled laboratory experiments were also conducted, with the objective of concurrently acquiring both the laser beam spatial characteristics in the forward direction and the laser backscatter temporal profile from each transmitted sub-nanosecond pulse. An artificial refractive index discontinuity was generated in clear test tank conditions by placing a clean ice-filled carboy above the laser beam propagation path. The results from both field and laboratory experiments confirm our hypothesis that turbulent layers are detectable by lidar sensors, and motivates that more research and lidar instrumentation development is needed to better quantify turbulence, especially for mitigating associated performance degrading effects for the U.S. Navy’s next generation electro-optic (EO) systems, including active laser imaging and laser communications.

PROCEEDINGS ARTICLE | June 12, 2012

Bahamas Optical Turbulence Exercise (BOTEX): preliminary results

Proc. SPIE. 8372, Ocean Sensing and Monitoring IV

KEYWORDS: Imaging systems, Scattering, Sensors, Water, Particles, Ocean optics, High speed cameras, Turbulence, Image transmission, Optical turbulence

The Bahamas Optical Turbulence Exercise (BOTEX) was conducted in the coastal waters of Florida and the Bahamas from June 30 to July 12 2011, onboard the R/V FG Walton Smith. The primary objective of the BOTEX was to obtain field measurements of optical turbulence structures, in order to investigate the impacts of the naturally occurring turbulence on underwater imaging and optical beam propagation. In order to successfully image through optical turbulence structures in the water and examine their impacts on optical transmission, a high speed camera and targets (both active and passive) were mounted on a rigid frame to form the Image Measurement Assembly for Subsurface Turbulence (IMAST). To investigate the impacts on active imaging systems such as the laser line scan (LLS), the Telescoping Rigid Underwater Sensor Structure (TRUSS) was designed and implemented by Harbor Branch Oceanographic Institute. The experiments were designed to determine the resolution limits of LLS systems as a function of turbulence induced beam wander at the target. The impact of natural turbulence structures on lidar backscatter waveforms was also examined, by means of a telescopic receiver and a short pulse transmitter, co-located, on a vertical profiling frame. To include a wide range of water types in terms of optical and physical conditions, data was collected from four different locations. . Impacts from optical turbulence were observed under both strong and weak physical structures. Turbulence measurements were made by two instruments, the Vertical Microstructure Profiler (VMP) and a 3D acoustical Doppler velocimeter with fast conductivity and temperature probes, in close proximity in the field. Subsequently these were mounted on the IMAST during moored deployments. The turbulence kinetic energy dissipation rate and the temperature dissipation rates were calculated from both setups in order to characterize the physical environments and their impacts. Beam deflection by multiple point patterns are examined, using high speed camera recordings (300 to 1200 fps), in association with measured turbulence structures. Initial results confirmed our hypothesis that turbulence impacted optical transmissions. They also showed that more research will be needed to better quantify and mitigate such effects, especially for the U.S. Navy's next generation EO systems, including active imaging, lidar and optical communications.

SPIE Conference Volume | June 11, 2012

Ocean Sensing and Monitoring IV

SPIE Journal Paper | May 21, 2012

Restoration of turbulence degraded underwater images

Kanaev, Andrey , Smith, Leslie , Hou, Weilin , Woods, Sarah

OE Vol. 51 Issue 5

KEYWORDS: Optical flow, Image fusion, Turbulence, Algorithm development, Image restoration, Image quality, Image filtering, Spatial frequencies, Reconstruction algorithms, Water

PROCEEDINGS ARTICLE | September 28, 2011

Multi-frame underwater image restoration

Proc. SPIE. 8185, Electro-Optical and Infrared Systems: Technology and Applications VIII

KEYWORDS: Image fusion, Spatial frequencies, Scattering, Image restoration, Image quality, Turbulence, Optical flow, Underwater imaging, Algorithm development, Motion estimation

PROCEEDINGS ARTICLE | September 28, 2011

Assessing EO image degradation from underwater optical turbulence in natural waters

Proc. SPIE. 8185, Electro-Optical and Infrared Systems: Technology and Applications VIII

KEYWORDS: Scattering, Water, Particles, Turbulence, Optical flow, Image enhancement, Modulation transfer functions, Algorithm development, Optical turbulence, Visibility

PROCEEDINGS ARTICLE | May 5, 2011

Quantifying turbulence microstructure for improvement of underwater imaging

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: Target detection, Scattering, Sensors, Water, Light scattering, Turbulence, Underwater imaging, Optical turbulence, Temperature metrology, Visibility

PROCEEDINGS ARTICLE | May 5, 2011

Automated detection and removal of cloud shadows on HICO images

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: Detection and tracking algorithms, Sensors, Water, Remote sensing, Reflectivity, Clouds, Ocean optics, Atmospheric corrections, Atmospheric sensing, Atmospheric optics

PROCEEDINGS ARTICLE | May 5, 2011

Impacts of optical turbulence on underwater imaging

Proc. SPIE. 8030, Ocean Sensing and Monitoring III

KEYWORDS: Optical transfer functions, Data modeling, Optical properties, Scattering, Water, Laser scattering, Turbulence, Modulation transfer functions, Underwater imaging, Optical turbulence

SPIE Conference Volume | May 4, 2011

Ocean Sensing and Monitoring III

PROCEEDINGS ARTICLE | April 20, 2010

Image feature detection and matching in underwater conditions

Proc. SPIE. 7678, Ocean Sensing and Monitoring II

KEYWORDS: Target detection, Point spread functions, Radon, Detection and tracking algorithms, Scattering, Sensors, Light scattering, Sensor performance, Underwater imaging, Algorithm development

PROCEEDINGS ARTICLE | April 20, 2010

Glider optical measurements and BUFR format for data QC and storage

Proc. SPIE. 7678, Ocean Sensing and Monitoring II

KEYWORDS: Optical sensors, Data modeling, Sensors, Data storage, Remote sensing, Optical testing, Ocean optics, Algorithm development, Environmental sensing, Binary data

PROCEEDINGS ARTICLE | April 20, 2010

TPDSci.com: a continually updated monograph of selected topics in the optics of turbid media

Proc. SPIE. 7678, Ocean Sensing and Monitoring II

KEYWORDS: Principal component analysis, Sensors, Particles, Light scattering, Photodiodes, Ocean optics, Near field, Navigation systems, Signal detection, Near field optics

SPIE Conference Volume | April 20, 2010

Ocean Sensing and Monitoring II

PROCEEDINGS ARTICLE | April 29, 2009

Diver visibility: Why one cannot see as far?

Proc. SPIE. 7317, Ocean Sensing and Monitoring

KEYWORDS: Optical transfer functions, Visual process modeling, Data modeling, Modulation, Spatial frequencies, Scattering, Particles, Turbulence, Underwater imaging, Visibility

SPIE Conference Volume | April 29, 2009

Ocean Sensing and Monitoring

PROCEEDINGS ARTICLE | September 24, 2007

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

Proc. SPIE. 6696, Applications of Digital Image Processing XXX

KEYWORDS: Signal to noise ratio, Point spread functions, Polarization, Optical properties, Imaging systems, Spatial frequencies, Scattering, Cameras, Modulation transfer functions, Absorption

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.

PROCEEDINGS ARTICLE | April 25, 2007

Objectively assessing underwater image quality for the purpose of automated restoration

Proc. SPIE. 6575, Visual Information Processing XVI

KEYWORDS: Signal to noise ratio, Edge detection, Wavelet transforms, Image compression, Scattering, Wavelets, Image restoration, Image quality, Image enhancement, Modulation transfer functions

PROCEEDINGS ARTICLE | February 6, 1997

Scattering phase function of very large particles in the ocean

Proc. SPIE. 2963, Ocean Optics XIII

KEYWORDS: Scattering, Signal attenuation, Water, Particles, Light scattering, Laser scattering, Ocean optics, Multiple scattering, Mie scattering, Scatter measurement

PROCEEDINGS ARTICLE | October 26, 1994

Some effects of the sensitivity threshold and spatial resolution of a particle imaging system on the shape of the measured particle size distribution

Proc. SPIE. 2258, Ocean Optics XII

KEYWORDS: Target detection, Digital image processing, Imaging systems, Image processing, Video, Particles, Image resolution, Ocean optics, Spatial resolution, Spherical lenses

PROCEEDINGS ARTICLE | December 31, 1992

Structured visible-diode-laser illumination for quantitative underwater imaging

Proc. SPIE. 1750, Ocean Optics XI

KEYWORDS: Mirrors, Fluctuations and noise, Signal attenuation, Image processing, Video, Particles, Semiconductor lasers, Ocean optics, Geometrical optics, Laser sintering

Showing 5 of 53 publications

Conference Committee Involvement (10)

Ocean Sensing and Monitoring X

17 April 2018 | Orlando, Florida, United States

Ocean Sensing and Monitoring IX

11 April 2017 | Anaheim, California, United States

Ocean Sensing and Monitoring VIII

19 April 2016 | Baltimore, Maryland, United States

Ocean Sensing and Monitoring VII

21 April 2015 | Baltimore, Maryland, United States

Ocean Sensing and Monitoring VI

6 May 2014 | Baltimore, Maryland, United States

Showing 5 of 10 published special sections

Course Instructor

SC1077: Ocean Sensing and Monitoring

This course covers basic principles and applications of optical oceanography. The course is aimed to provide background information for those interested in exploring processes involving the ocean using optical techniques, including sensing and monitoring via remotely (passive and active), as well as traditional in situ measurement and sampling approaches. A brief introduction of oceanography will be given, followed by ocean optics principles include scattering by both particles and optical turbulence, polarization and impacts on underwater imaging and communication, through theoretical frame work and examples. Typical sensors and platforms including unmanned underwater vehicles are introduced. Topics associated with data collection, processing, analysis, fusion and assimilation to ocean models are also discussed. This course can also be used as a refresher for recent advances in related areas. This course helps to understand apply to research and development efforts relevant to the maritime environment, in such issues as sea surface temperature sensing, underwater imaging, and remote sensing including water quality monitoring related to biological activities or extreme events, for example.

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