A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome

In the present study, multilayer perceptron (MLP) neural networks were applied to help in the diagnosis of obstructive sleep apnoea syndrome (OSAS). Oxygen saturation (SaO2) recordings from nocturnal pulse oximetry were used for this purpose. We performed time and spectral analysis of these signals to extract 14 features related to OSAS. The performance of two different MLP classifiers was compared: maximum likelihood (ML) and Bayesian (BY) MLP networks. A total of 187 subjects suspected of suffering from OSAS took part in the study. Their SaO2 signals were divided into a training set with 74 recordings and a test set with 113 recordings. BY-MLP networks achieved the best performance on the test set with 85.58% accuracy (87.76% sensitivity and 82.39% specificity). These results were substantially better than those provided by ML-MLP networks, which were affected by overfitting and achieved an accuracy of 76.81% (86.42% sensitivity and 62.83% specificity). Our results suggest that the Bayesian framework is preferred to implement our MLP classifiers. The proposed BY-MLP networks could be used for early OSAS detection. They could contribute to overcome the difficulties of nocturnal polysomnography (PSG) and thus reduce the demand for these studies.

Evaluation of remote sensing for the detection of landfill gas and leachate in an urban environment

The technique of remote sensing provides a unique view of the earth's surface and considerable areas can be surveyed in a short amount of time. The aim of this project was to evaluate whether remote sensing, particularly using the Airborne Thematic Mapper (ATM) with its wide spectral range, was capable of monitoring landfill sites within an urban environment with the aid of image processing and Geographical Information Systems (GIS) methods. The regions under study were in the West Midlands conurbation and consisted of a large area in what is locally known as the Black Country containing heavy industry intermingled with residential areas, and a large single active landfill in north Birmingham. When waste is collected in large volumes it decays and gives off pollutants. These pollutants, landfill gas and leachate (a liquid effluent), are known to be injurious to vegetation and can cause stress and death. Vegetation under stress can exhibit a physiological change, detectable by the remote sensing systems used. The chemical and biological reactions that create the pollutants are exothermic and the gas and leachate, if they leave the waste, can be warmer than their surroundings. Thermal imagery from the ATM (daylight and dawn) and thermal video were obtained and used to find thermal anomalies on the area under study. The results showed that vegetation stress is not a reliable indicator of landfill gas migration, as sites within an urban environment have a cover too complex for the effects to be identified. Gas emissions from two sites were successfully detected by all the thermal imagery with the thermal ATM being the best. Although the results were somewhat disappointing, recent technical advancements in the remote sensing systems used in this project would allow geo-registration of ATM imagery taken on different occasions and the elimination of the effects of solar insolation.

Effects of pixel noise and stimulus structure on visual detection performance

This thesis consisted of two major parts, one determining the masking characteristics of pixel noise and the other investigating the properties of the detection filter employed by the visual system. The theoretical cut-off frequency of white pixel noise can be defined from the size of the noise pixel. The empirical cut-off frequency, i.e. the largest size of noise pixels that mimics the effect of white noise in detection, was determined by measuring contrast energy thresholds for grating stimuli in the presence of spatial noise consisting of noise pixels of various sizes and shapes. The critical i.e. minimum number of noise pixels per grating cycle needed to mimic the effect of white noise in detection was found to decrease with the bandwidth of the stimulus. The shape of the noise pixels did not have any effect on the whiteness of pixel noise as long as there was at least the minimum number of noise pixels in all spatial dimensions. Furthermore, the masking power of white pixel noise is best described when the spectral density is calculated by taking into account all the dimensions of noise pixels, i.e. width, height, and duration, even when there is random luminance only in one of these dimensions. The properties of the detection mechanism employed by the visual system were studied by measuring contrast energy thresholds for complex spatial patterns as a function of area in the presence of white pixel noise. Human detection efficiency was obtained by comparing human performance with an ideal detector. The stimuli consisted of band-pass filtered symbols, uniform and patched gratings, and point stimuli with randomised phase spectra. In agreement with the existing literature, the detection performance was found to decline with the increasing amount of detail and contour in the stimulus. A measure of image complexity was developed and successfully applied to the data. The accuracy of the detection mechanism seems to depend on the spatial structure of the stimulus and the spatial spread of contrast energy.

MAP detection for impairment compensation in coherent WDM systems

We propose a novel recursive-algorithm based maximum a posteriori probability (MAP) detector in spectrally-efficient coherent wavelength division multiplexing (CoWDM) systems, and investigate its performance in a 1-bit/s/Hz on-off keyed (OOK) system limited by optical-signal-to-noise ratio. The proposed method decodes each sub-channel using the signal levels not only of the particular sub-channel but also of its adjacent sub-channels, and therefore can effectively compensate deterministic inter-sub-channel crosstalk as well as inter-symbol interference arising from narrow-band filtering and chromatic dispersion (CD). Numerical simulation of a five-channel OOK-based CoWDM system with 10Gbit/s per channel using either direct or coherent detection shows that the MAP decoder can eliminate the need for phase control of each optical carrier (which is necessarily required in a conventional CoWDM system), and greatly relaxes the spectral design of the demultiplexing filter at the receiver. It also significantly improves back-to-back sensitivity and CD tolerance of the system.

Aptamer-based surface plasmon sensor for thrombin detection

A series of surface plasmonic fibre devices were fabricated using multiple coatings deposited on a lapped section of a single mode fibre and post-fabrication UV laser irradiation processing with a phase mask, producing a surface relief grating structure. These devices showed high spectral sensitivity in the aqueous index regime ranging up to 4000 nm/RIU for wavelength and 800 dB/RIU for intensity. The devices were then coated with human thrombin binding aptamer. Several concentrations of thrombin in buffer solution were made, ranging from 1nM to 1µM. All the concentrations were detectable by the devices demonstrating that sub-nM concentrations may be monitored.

Side detection of strong radiation-mode out-coupling from blazed FBGs in single-mode and multimode fibers

We report on the effective side detection of radiation-mode out-coupling from blazed fiber Bragg gratings (BFBGs) fabricated in single-mode fiber (SMF) and multimode fiber (MMF). The far-field radiation power distribution from BFBGs have been measured achieving a high spatial-spectral resolution (0.17 mm/nm). We have also investigated comparatively the transmission-loss characteristics of BFBGs in both fiber types, fabricated using phase-mask and holographic inscription techniques. Our results reveal clearly that the radiation out-coupling from BFBGs is significantly stronger and spectrally more confined in MMF than in SMF.

A sensing mechanism for the detection of carbon nanotubes using selective photoluminescent probes based on ionic complexes with organic dyes

The multifunctional properties of carbon nanotubes (CNTs) make them a powerful platform for unprecedented innovations in a variety of practical applications. As a result of the surging growth of nanotechnology, nanotubes present a potential problem as an environmental pollutant, and as such, an efficient method for their rapid detection must be established. Here, we propose a novel type of ionic sensor complex for detecting CNTs – an organic dye that responds sensitively and selectively to CNTs with a photoluminescent signal. The complexes are formed through Coulomb attractions between dye molecules with uncompensated charges and CNTs covered with an ionic surfactant in water. We demonstrate that the photoluminescent excitation of the dye can be transferred to the nanotubes, resulting in selective and strong amplification (up to a factor of 6) of the light emission from the excitonic levels of CNTs in the near-infrared spectral range, as experimentally observed via excitation-emission photoluminescence (PL) mapping. The chirality of the nanotubes and the type of ionic surfactant used to disperse the nanotubes both strongly affect the amplification; thus, the complexation provides sensing selectivity towards specific CNTs. Additionally, neither similar uncharged dyes nor CNTs covered with neutral surfactant form such complexes. As model organic molecules, we use a family of polymethine dyes with an easily tailorable molecular structure and, consequently, tunable absorbance and PL characteristics. This provides us with a versatile tool for the controllable photonic and electronic engineering of an efficient probe for CNT detection.

Biosensor based on excessively tilted fiber grating in thin-cladding optical fiber for sensitive and selective detection of low glucose concentration

We report a highly sensitive, high Q-factor, label free and selective glucose sensor by using excessively tilted fiber grating (Ex-TFG) inscribed in the thin-cladding optical fiber (TCOF). Glucose oxidase (GOD) was covalently immobilized on optical fiber surface and the effectiveness of GOD immobilization was investigated by the fluorescence microscopy and highly accurate spectral interrogation method. In contrast to the long period grating (LPG) and optical fiber (OF) surface Plasmon resonance (SPR) based glucose sensors, the Ex-TFG configuration has merits of nearly independent cross sensitivity of the environmental temperature, simple fabrication method (no noble metal deposition or cladding etching) and high detection accuracy (or Q-factor). Our experimental results have shown that Ex-TFG in TCOF based sensor has a reliable and fast detection for the glucose concentration as low as 0.1~2.5mg/ml and a high sensitivity of ~1.514nm·(mg/ml)−1, which the detection accuracy is ~0.2857nm−1 at pH 5.2, and the limit of detection (LOD) is 0.013~0.02mg/ml at the pH range of 5.2~7.4 by using an optical spectrum analyzer with a resolution of 0.02nm.

Localized surface plasmon fiber device coated with carbon nanotubes for the specific detection of CO2

We explored the potential of a carbon nanotube (CNT) coating working in conjunction with a recently developed localized surface plasmon (LSP) device (based upon a nanostructured thin film consisting of of nano-wires of platinum) with ultra-high sensitivity to changes in the surrounding index. The uncoated LSP sensor’s transmission resonances exhibited a refractive index sensitivity of Δλ/Δn ~ -6200nm/RIU and ΔΙ/Δn ~5900dB/RIU, which is the highest reported spectral sensitivity of a fiber optic sensor to bulk index changes within the gas regime. The complete device provides the first demonstration of the chemically specific gas sensing capabilities of CNTs utilizing their optical characteristics. This is proven by investigating the spectral response of the sensor before and after the adhesion of CNTs to alkane gases along with carbon dioxide. The device shows a distinctive spectral response in the presence of gaseous CO2 over and above what is expected from general changes in the bulk refractive index. This fiber device yielded a limit of detection of 150ppm for CO2 at a pressure of one atmosphere. Additionally the adhered CNTs actually reduce sensitivity of the device to changes in bulk refractive index of the surrounding medium. The polarization properties of the LSP sensor resonances are also investigated and it is shown that there is a reduction in the overall azimuthal polarization after the CNTs are applied. These optical devices offer a way of exploiting optically the chemical selectivity of carbon nanotubes, thus providing the potential for real-world applications in gas sensing in many inflammable and explosive environments. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Scaling multimode fibre IM/DD transmission capacity through spatial-spectral multiplexing

Data centre connections can greatly benefit from parallel transmission channels on one multimode fibre (MMF). Shortwave wavelength division multiplexing (SWDM) achieves parallel transmission through spectral multiplexing. Furthermore, MMFs offer a spatial dimension that should be exploited to increase parallel transmission, albeit in a cost-effective way. In this paper, it is shown that SWDM and spatial multiplexing can be combined in intensity modulation and direct detection MMF transmission systems that use selective offset excitation and mode-selective spatial filtering.