Bing Ouyang

Image enhancement for underwater pulsed laser line scan imaging system

Recent progress in system hardware such as laser, photon detectors and other electronic and optical components resulted in significant improvement for the underwater serial laser imaging system. Nevertheless, during normal system operation, system issues such as laser instability, electronic noise, and environmental conditions such as imaging in highly turbid water can still put constraint on the performance of imager. In this work, post-processing to take advantage of the improvement hardware to further reduce image noise and enhance the image quality as a critical aspect of the overall system design is studied. A novel realization of the bilateral principle based image/pulse noise reduction and image deconvolution using point spread function (PSF) predicted with EODES radiative transfer model is used to implement the processing chain. The concept is further extended to a multichannel deconvolution to exploit the benefit offered by the new multi element PMT configuration developed in HBOI. Two datasets were used to test the developed techniques respectively.

Extended-Range Undersea Laser Imaging: Current Research Status and a Glimpse at Future Technologies

Recent advancements in obtaining visibility of undersea objects at extended ranges in coastal and oceanic waters are reviewed for the years 2009 to present. The paper focuses on the latest techniques that are utilized to reduce the undesirable effects of scattering, mainly due to suspended particulate within the imaging volume, leading to the loss of contrast and blurring characteristic of undersea optical images produced over long ranges. Several recent sets of experimental results obtained using both benchtop laboratory development systems as well as field-deployable prototypes of new system concepts are presented, with observed performance attributes being discussed. Simulation studies that make use of accurate radiative transfer physical models to enable design and operation of new system concepts within a turbid water environment are also presented. Finally, this paper includes a description and results from an extended-range laser system that has reached a level of packaging and automation necessary to be available as a commercial product.

Visualization and Image Enhancement for Multistatic Underwater Laser Line Scan System Using Image-Based Rendering

Over the last several decades, developments in underwater laser line scan (LLS) serial imaging sensors have resulted in significant improvements in turbid water imaging performance. In the last few years, there has been renewed interest in distributed, truly multistatic time-varying intensity (TVI) (i.e., multiple transmitter nonsynchronous LLS) sensor configurations. In addition to being capable of high-quality image acquisition through tens of beam attenuation lengths, while simultaneously establishing a non-line-of-sight free-space communications link, these system architectures also have the potential to provide a more synoptic image coverage of larger regions of seabed and the flexibility to simultaneously examine a target from different perspectives. A related issue worth investigation is how to utilize these capabilities to improve rendering of the underwater scenes. In this regard, light field rendering (LFR)-a type of image-based rendering (IBR) technique-offers several advantages. Compared to other IBR techniques, LFR can provide signal-to-noise ratio (SNR) improvements and the ability to image through obscuring objects in front of the target. On the other hand, multistatic nonsynchronous LLS can be readily configured to acquire image sequences needed to generate LFR. This paper investigates the application of LFR to images taken from a distributed bistatic nonsynchronous LLS imager using both line-ofsight and non-line-of-sight imaging geometries to create multiperspective rendering of an unknown underwater scene. The issues related to effectively applying this technique to underwater LLS imagery are analyzed and an image postprocessing flow to address these issues is proposed. The results from a series of experiments at the Harbor Branch Oceanographic Institute at the Florida Atlantic University (HBOI-FAU, Fort Pierce, FL, USA) optical imaging test tank demonstrated the capability of using bistatic/multistatic nonsynchronous LLS system to generated LFR and, therefore, verify the proposed image processing flow. The benefits of LFR to underwater imaging in challenging environments were further demonstrated via imaging against a variety of obstacles such as mesh screens, bubbles, and water at different turbidity. Image quality metrics based on mutual information and texture features were used in the analysis of the experimental results.

Marine animal classification using combined CNN and hand-designed image features

Digital imagery and video have been widely used in many undersea applications. Online automated labeling of marine animals in such video clips comprises of three major steps: detection and tracking, feature extraction and classification. The latter two aspects are the focus of this paper. Feature extracted from convolutional neural network (CNN) is tested on two real-world marine animal datasets (Taiwan sea fish and Monterey Bay Aquarium Research Institute (MBARI) benthic animal), and yields better classification results than existing approaches. Appropriate combination of CNN and hand-designed features can achieve even higher accuracy than applying CNN alone. The group feature selection scheme, which is a modified version of the minimal-redundancy-maximal-relevance (mRMR) algorithm, serves as the criterion for selecting an optimal set of hand-designed features. Performance of CNN and hand-designed features are further examined for images with lowered quality that emulates bad lighting condition in water.

Extended range distributed laser serial imaging in turbid estuarine and coastal conditions

One pressing need in the drive to better secure the coastal environment and associated natural and manmade assets is the ability to rapidly identify suspicious undersea objects. Typically murky harbor and coastal waters render this task nearly impossible, even with the most sophisticated underwater camera technologies. However, simpler system architectures that can extend operational range and also rapidly transmit high-quality imagery and other information to remote locations could be realized if a serial laser illuminator and single element detector sub-systems are operated in a distributed configuration, possibly among multiple undersea robotic platforms. To gain a better understanding of the potential performance of this distributed undersea imaging technique in natural waters, and also to determine if precise alignment is required between laser illuminator and detector sub-systems during such operations, the Ocean Visibility and Optics Laboratory at Harbor Branch Oceanographic Institute recently developed a prototype distributed laser imager. The system was tested recently in a range of very turbid estuarine conditions off the east coast of Florida. Results from these experiments as well as a description of this distributed laser imager prototype will be presented and discussed in this paper.

Physical layer simulator for undersea free-space laser communications

Abstract. High bandwidth (10 to 100 Mbps), real-time data networking in the subsea environment using free-space lasers has a potentially high impact as an enabling technology for a variety of future subsea operations in the areas of distributed sensing, real-time wireless data transfer, control of unmanned undersea vehicles, and other submerged assets. However, the development and testing of laser networking equipment in the undersea environment are expensive and time consuming, and there is a clear need for a network simulation framework that will allow researchers to evaluate the performance of alternate optical and electronic configurations under realistic operational and environmental constraints. The overall objective of the work reported in this paper was to develop and validate such a simulation framework, which consists of (1) a time-dependent radiative transfer model to accurately predict the channel impulse characteristics for alternate system designs over a range of geometries and optical properties and (2) digital modulation and demodulation blocks which accurately simulate both laser source and receiver noise characteristics in order to generate time domain bit stream samples that can be digitally demodulated to predict the resulting bit error rate of the simulated link.

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.

Compressive sensing underwater laser serial imaging system

Abstract. Compressive sensing (CS) theory has drawn great interest in recent years and has led to new image-acquisition techniques in many different fields. This research investigates a CS-based active underwater laser serial imaging system, which employs a spatial light modulator (SLM) at the source. A multiscale polarity-flipping measurement matrix and a model-assisted image reconstruction concept are proposed to address limitations imposed by a scattering medium. These concepts are also applicable to CS-based imaging in atmospheric environments characterized by fog, rain, or clouds. Simulation results comparing the performance of the proposed technique with that of traditional laser line scan (LLS) sensors and other structured illumination-based imager are analyzed. Experimental results from over-the-air and underwater tests are also presented. The potential for extending the proposed frame-based imaging technique to the traditional line-by-line scanning mode is discussed.

Visualization for multi-static underwater LLS system using Image Based Rendering

Over the last several decades developments in Underwater Laser Line Scan (LLS) systems have resulted in significant improvements in turbid water imaging performance. In addition to allowing for high quality image acquisition through tens of attenuation lengths, the recently renewed interest in multiple platform distributed LLS configurations also has the potential for synoptic coverage of much larger regions of seabed. A related issue worth investigation is how to utilize these capabilities to improve rendering of the underwater scenes. In this regard, Light Field Rendering (LFR) - a type of Image Based Rendering (IBR) technique offers several advantages. LFR enables multi-perspective target visualization without measuring the geometrical dimension of the target. Compared to other IBR techniques, LFR can provide Signal-to-Noise Ratio (SNR) improvements and the ability to image through obscuring objects in front of the target. On the other hand, multi-static LLS can be readily configured to acquired images to generate LFR. This paper investigates the application of LFR to images taken from a distributed bi-static LLS imager to create multi-perspective rendering of an unknown underwater scene. The issues related to effectively applying this technique to underwater LLS imagery are analyzed and image post-processing flow to addresses these issues are proposed. An experiment was conducted in FAU-HBOI optical imaging test tank, the results from which demonstrated the capability of using bi-static/multi-static LLS system to generated LFR and also verified the proposed image processing flow. The aforementioned benefits of LFR were also presented.

Information point set registration for shape recognition

This paper proposes a way of enhancing shape recognition through point set registration. Firstly, a modified version of shape context (SC) is developed, which is invariant to rigid transformation and flipping. With the point correspondence obtained by the modified SC, an affine transformation based on the maximum correntropy criterion (MCC) is performed on the query shape. This point set registration could be further refined by non-rigid morphing with the minimization of Cauchy-Schwarz divergence (DCS). Not only does this information theoretical learning (ITL) approach renders excellent registration result, but a new shape similarity measure can also be derived from the registration.