反射と蛍光を含むシーンの分光特性モデリング

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 相澤 清晴, 東京大学教授 佐藤 洋一, 東京大学教授 佐藤 真一, 東京大学准教授 山崎 俊彦, 東京大学准教授 大石 岳史University of Tokyo(東京大学

Hyperspectral benthic mapping from underwater robotic platforms

We live on a planet of vast oceans; 70% of the Earth's surface is covered in water. They are integral to supporting life, providing 99% of the inhabitable space on Earth. Our oceans and the habitats within them are under threat due to a variety of factors. To understand the impacts and possible solutions, the monitoring of marine habitats is critically important. Optical imaging as a method for monitoring can provide a vast array of information however imaging through water is complex. To compensate for the selective attenuation of light in water, this thesis presents a novel light propagation model and illustrates how it can improve optical imaging performance. An in-situ hyperspectral system is designed which comprised of two upward looking spectrometers at different positions in the water column. The downwelling light in the water column is continuously sampled by the system which allows for the generation of a dynamic water model. In addition to the two upward looking spectrometers the in-situ system contains an imaging module which can be used for imaging of the seafloor. It consists of a hyperspectral sensor and a trichromatic stereo camera. New calibration methods are presented for the spatial and spectral co-registration of the two optical sensors. The water model is used to create image data which is invariant to the changing optical properties of the water and changing environmental conditions. In this thesis the in-situ optical system is mounted onboard an Autonomous Underwater Vehicle. Data from the imaging module is also used to classify seafloor materials. The classified seafloor patches are integrated into a high resolution 3D benthic map of the surveyed site. Given the limited imaging resolution of the hyperspectral sensor used in this work, a new method is also presented that uses information from the co-registered colour images to inform a new spectral unmixing method to resolve subpixel materials

High Efficiency and Wide Color Gamut Liquid Crystal Displays

Liquid crystal display (LCD) has become ubiquitous and indispensable in our daily life. Recently, it faces strong competition from organic light emitting diode (OLED). In order to maintain a strong leader position, LCD camp has an urgent need to enrich the color performance and reduce the power consumption. This dissertation focuses on solving these two emerging and important challenges. In the first part of the dissertation we investigate the quantum dot (QD) technology to improve the both the color gamut and the light efficiency of LCD. QD emits saturated color and grants LCD the capability to reproduce color vivid images. Moreover, the QD emission spectrum can be custom designed to match to transmission band of color filters. To fully take advantage of QD\u27s unique features, we propose a systematic modelling of the LCD backlight and optimize the QD spectrum to simultaneously maximize the color gamut and light efficiency. Moreover, QD enhanced LCD demonstrates several advantages: excellent ambient contrast, negligible color shift and controllable white point. Besides three primary LCD, We also present a spatiotemporal four-primary QD enhanced LCD. The LCD\u27s color is generated partially from time domain and partially from spatial domain. As a result, this LCD mode offers 1.5× increment in spatial resolution, 2× brightness enhancement, slightly larger color gamut and mitigated LC response requirement (~4ms). It can be employed in the commercial TV to meet the challenging Energy star 6 regulation. Besides conventional LCD, we also extend the QD applications to liquid displays and smart lighting devices. The second part of this dissertation focuses on improving the LCD light efficiency. Conventional LCD system has fairly low light efficiency (4%~7%) since polarizers and color filters absorb 50% and 67% of the incoming light respectively. We propose two approaches to reduce the light loss within polarizers and color filters. The first method is a polarization preserving backlight system. It can be combined with linearly polarized light source to boost the LCD efficiency. Moreover, this polarization preserving backlight offers high polarization efficiency (~77.8%), 2.4× on-axis luminance enhancement, and no need for extra optics films. The second approach is a LCD backlight system with simultaneous color/polarization recycling. We design a novel polarizing color filter with high transmittance ( \u3e 90%), low absorption loss (~3.3%), high extinction ratio (\u3e10,000:1) and large angular tolerance (up to ±50˚). This polarizing color filter can be used in LCD system to introduce the color/polarization recycling and accordingly boost LCD efficiency by ~3 times. These two approaches open new gateway for ultra-low power LCDs. In the final session of this dissertation, we demonstrate a low power and color vivid reflective liquid crystal on silicon (LCOS) display with low viscosity liquid crystal mixture. Compared with commercial LC material, the new LC mixture offers ~4X faster response at 20oC and ~8X faster response at -20°C. This fast response LC material enables the field-sequential-color (FSC) driving for power saving. It also leads to several attractive advantages: submillisecond response time at room temperature, vivid color even at -20oC, high brightness, excellent ambient contrast ratio, and suppressed color breakup. With this material improvement, LCOS display can be promising for the emerging wearable display market

2015 Oil Observing Tools: A Workshop Report

Since 2010, the National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) have provided satellite-based pollution surveillance in United States waters to regulatory agencies such as the United States Coast Guard (USCG). These technologies provide agencies with useful information regarding possible oil discharges. Unfortunately, there has been confusion as to how to interpret the images collected by these satellites and other aerial platforms, which can generate misunderstandings during spill events. Remote sensor packages on aircraft and satellites have advantages and disadvantages vis-à-vis human observers, because they do not “see” features or surface oil the same way. In order to improve observation capabilities during oil spills, applicable technologies must be identified, and then evaluated with respect to their advantages and disadvantages for the incident. In addition, differences between sensors (e.g., visual, IR, multispectral sensors, radar) and platform packages (e.g., manned/unmanned aircraft, satellites) must be understood so that reasonable approaches can be made if applicable and then any data must be correctly interpreted for decision support. NOAA convened an Oil Observing Tools Workshop to focus on the above actions and identify training gaps for oil spill observers and remote sensing interpretation to improve future oil surveillance, observation, and mapping during spills. The Coastal Response Research Center (CRRC) assisted NOAA’s Office of Response and Restoration (ORR) with this effort. The workshop was held on October 20-22, 2015 at NOAA’s Gulf of Mexico Disaster Response Center in Mobile, AL. The expected outcome of the workshop was an improved understanding, and greater use of technology to map and assess oil slicks during actual spill events. Specific workshop objectives included: •Identify new developments in oil observing technologies useful for real-time (or near real-time) mapping of spilled oil during emergency events. •Identify merits and limitations of current technologies and their usefulness to emergency response mapping of oil and reliable prediction of oil surface transport and trajectory forecasts.Current technologies include: the traditional human aerial observer, unmanned aircraft surveillance systems, aircraft with specialized senor packages, and satellite earth observing systems. •Assess training needs for visual observation (human observers with cameras) and sensor technologies (including satellites) to build skills and enhance proper interpretation for decision support during actual events

Surface analysis and visualization from multi-light image collections

Multi-Light Image Collections (MLICs) are stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination that provides large amounts of visual and geometric information. Over the last decades, a wide variety of methods have been devised to extract information from MLICs and have shown its use in different application domains to support daily activities. In this thesis, we present methods that leverage a MLICs for surface analysis and visualization. First, we provide background information: acquisition setup, light calibration and application areas where MLICs have been successfully used for the research of daily analysis work. Following, we discuss the use of MLIC for surface visualization and analysis and available tools used to support the analysis. Here, we discuss methods that strive to support the direct exploration of the captured MLIC, methods that generate relightable models from MLIC, non-photorealistic visualization methods that rely on MLIC, methods that estimate normal map from MLIC and we point out visualization tools used to do MLIC analysis. In chapter 3 we propose novel benchmark datasets (RealRTI, SynthRTI and SynthPS) that can be used to evaluate algorithms that rely on MLIC and discusses available benchmark for validation of photometric algorithms that can be also used to validate other MLIC-based algorithms. In chapter 4, we evaluate the performance of different photometric stereo algorithms using SynthPS for cultural heritage applications. RealRTI and SynthRTI have been used to evaluate the performance of (Neural)RTI method. Then, in chapter 5, we present a neural network-based RTI method, aka NeuralRTI, a framework for pixel-based encoding and relighting of RTI data. In this method using a simple autoencoder architecture, we show that it is possible to obtain a highly compressed representation that better preserves the original information and provides increased quality of virtual images relighted from novel directions, particularly in the case of challenging glossy materials. Finally, in chapter 6, we present a method for the detection of crack on the surface of paintings from multi-light image acquisitions and that can be used as well on single images and conclude our presentation

Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future