Efficient Algorithms for Light Transmission, Focusing and Scattering Matrix Retrieval in Highly Diffusive 3D Random Media

Wavefront shaping provides an increasingly appealing avenue for imaging and other applications that require controlling electromagnetic waves passing through complex and disordered media. Indeed, these techniques allow researchers and engineers to exploit the properties of high-frequency waves, particularly optical ones, as they interact with these media to obtain nearly perfect transmission and a high degree of focusing. Here, we simulate the process of wave propagation in 3D random media using full-wave, integral equation-based computational electromagnetics schemes. We replicate many experimental observations relating to the existence of so-called open channels in non-absorbing random media and the distribution of their transmission coefficients. In addition, we develop new schemes for manipulating these waves, e.g. by focusing them onto one or multiple spots in the output plane. Furthermore, we leverage the computational methods to develop new schemes for characterizing random media, e.g. by computing their scattering and transmission matrices under a variety of conditions. Finally, we study the transmission properties of absorbing media and find a universal fluctuant pattern of their maximal transmission coefficients.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147580/1/hanguo_1.pd

Holographic Imaging and Iterative Phase Optimization Methods for Focusing and Transmitting Light in Scattering Media.

Existing methods for focusing and imaging through strongly scattering materials are often limited by speed, the need for invasive feedback, and the shallow depth of penetration of photons into the material. These limitations have motivated the present research into the development of a new iterative phase optimization method for improving transmission of light through a sample of strongly scattering material. A new method, based on the detection of back-scattered light combined with active (phase-only) wavefront control was found to be partially successful, decreasing the power of backscattered incident light at 488 nm wavelength by approximately 35% in a 626 μm thick sample of Yttria (Y2O3) nanopowder (mean particle size 26 nm) in clear epoxy with transport mean free path length ~116 μm. However, the observed transmitted power did not show simultaneous improvement. The conclusion was reached that scattering to the sides of the sample and polarization scrambling were responsible for the lack of improved transmission with this method. Some ideas for improvement are discussed in the thesis. This research subsequently led to the development of a lensless holographic imaging method based on a rotating diffuser for statistical averaging of the optical signal for overcoming speckle caused by reflection from a rough surface. This method made it possible to reduce background variations of intensity due to speckle and improve images reflected from rough, immobile surfaces with no direct path for photons between the object and camera. Improvements in the images obtained with this technique were evaluated quantitatively by comparing SSIM indices and were found to offer practical advances for transmissive and reflective geometries alike.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135741/1/mjpur_1.pd

Underwater image restoration: super-resolution and deblurring via sparse representation and denoising by means of marine snow removal

Underwater imaging has been widely used as a tool in many fields, however, a major issue is the quality of the resulting images/videos. Due to the light's interaction with water and its constituents, the acquired underwater images/videos often suffer from a significant amount of scatter (blur, haze) and noise. In the light of these issues, this thesis considers problems of low-resolution, blurred and noisy underwater images and proposes several approaches to improve the quality of such images/video frames. Quantitative and qualitative experiments validate the success of proposed algorithms

New Methods and Theory for Increasing Transmission of Light through Highly-Scattering Random Media.

Scattering hinders the passage of light through random media and consequently limits the usefulness of optical techniques for sensing and imaging. Thus, methods for increasing the transmission of light through such random media are of interest. Against this backdrop, recent theoretical and experimental advances have suggested the existence of a few highly transmitting eigen-wavefronts with transmission coefficients close to one in strongly backscattering random media. Here, we numerically analyze this phenomenon in 2-D with fully spectrally accurate simulators and provide the first rigorous numerical evidence confirming the existence of these highly transmitting eigen-wavefronts in random media with periodic boundary conditions that is composed of hundreds of thousands of non-absorbing scatterers. We then develop physically realizable algorithms for increasing the transmission and the focusing intensity through such random media using backscatter analysis. Also, we develop physically realizable iterative algorithms using phase-only modulated wavefronts and non-iterative algorithms for increasing the transmission through such random media using backscatter analysis. We theoretically show that, despite the phase-only modulation constraint, the non-iterative algorithms will achieve at least about 78.5%. We show via numerical simulations that the algorithms converge rapidly, yielding a near-optimum wavefront in just a few iterations. Finally, we theoretically analyze this phenomenon of perfect transmission and provide the first mathematically, justified random matrix model for such scattering media that can accurately predict the transmission coefficient distribution so that the existence of an eigen-wavefront with transmission coefficient approaching one for random media can be rigorously analyzed.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107051/1/jsirius_1.pd

Radiometric correction of scatterometric wind measurements

Use of a spaceborne scatterometer to determine the ocean-surface wind vector requires accurate measurement of radar backscatter from ocean. Such measurements are hindered by the effect of attenuation in the precipitating regions over sea. The attenuation can be estimated reasonably well with the knowledge of brightness temperatures observed by a microwave radiometer. The NASA SeaWinds scatterometer is to be flown on the Japanese ADEOS2. The AMSR multi-frequency radiometer on ADEOS2 will be used to correct errors due to attenuation in the SeaWinds scatterometer measurements. Here we investigate the errors in the attenuation corrections. Errors would be quite small if the radiometer and scatterometer footprints were identical and filled with uniform rain. However, the footprints are not identical, and because of their size one cannot expect uniform rain across each cell. Simulations were performed with the SeaWinds scatterometer (13.4 GHz) and AMSR (18.7 GHz) footprints with gradients of attenuation. The study shows that the resulting wind speed errors after correction (using the radiometer) are small for most cases. However, variations in the degree of overlap between the radiometer and scatterometer footprints affect the accuracy of the wind speed measurements

Review Article: Global Monitoring of Snow Water Equivalent Using High-Frequency Radar Remote Sensing

Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth\u27s surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth\u27s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world\u27s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth\u27s cold regions\u27 ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements