Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

The development of calibration and adaptive filtering procedures for neuromagnetic studies of human visual function

This thesis first considers the calibration and signal processing requirements of a neuromagnetometer for the measurement of human visual function. Gradiometer calibration using straight wire grids is examined and optimal grid configurations determined, given realistic constructional tolerances. Simulations show that for gradiometer balance of 1:104 and wire spacing error of 0.25mm the achievable calibration accuracy of gain is 0.3%, of position is 0.3mm and of orientation is 0.6°. Practical results with a 19-channel 2nd-order gradiometer based system exceed this performance. The real-time application of adaptive reference noise cancellation filtering to running-average evoked response data is examined. In the steady state, the filter can be assumed to be driven by a non-stationary step input arising at epoch boundaries. Based on empirical measures of this driving step an optimal progression for the filter time constant is proposed which improves upon fixed time constant filter performance. The incorporation of the time-derivatives of the reference channels was found to improve the performance of the adaptive filtering algorithm by 15-20% for unaveraged data, falling to 5% with averaging. The thesis concludes with a neuromagnetic investigation of evoked cortical responses to chromatic and luminance grating stimuli. The global magnetic field power of evoked responses to the onset of sinusoidal gratings was shown to have distinct chromatic and luminance sensitive components. Analysis of the results, using a single equivalent current dipole model, shows that these components arise from activity within two distinct cortical locations. Co-registration of the resulting current source localisations with MRI shows a chromatically responsive area lying along the midline within the calcarine fissure, possibly extending onto the lingual and cuneal gyri. It is postulated that this area is the human homologue of the primate cortical area V4.

Transmission comparison of ultra-long Raman fibre laser based amplification with first and dual order Raman amplification using 10×118 Gbit/s DP-QPSK

Experimental investigations of 10×118 Gbit/s DP-QPSK WDM transmission using three types of distributed Raman amplification techniques are presented. Novel ultra-long Raman fibre laser based amplification with second order counter-propagated pumping is compared with conventional first order and dual order counter-pumped Raman amplification. We demonstrate that URFL based amplification can extend the transmission reach up to a distance of 7520 km in comparison with 5010 km and 6180 km using first order and dual order Raman amplification respectively. © 2014 IEEE.

Analytical characterization of a quasi-lossless Raman-amplified fibre transmission scheme

In this paper, we explore theoretically a novel amplifier scheme, that combines second order bidirectional pumping and fiber Bragg grating reflectors to achieve quasi-lossless transmission over long spans. The scheme is shown to significantly reduce the signal power variation over the span as compared to commonly used schemes with the same number of pump sources. It is concluded that it can be practical to analyze a simplified system of three equations, obtained by neglecting noise terms, that would allow us to better understand the physical mechanisms and to find analytical estimates for the required pump power or the power variations along the fibre span

Amplification schemes and multi-channel DBP for unrepeatered transmission

The performance of unrepeatered transmission of a seven Nyquist-spaced 10 GBd PDM-16QAM superchannel using full signal band coherent detection and multi-channel digital back propagation (MC-DBP) to mitigate nonlinear effects is analysed. For the first time in unrepeatered transmission, the performance of two amplification systems is investigated and directly compared in terms of achievable information rates (AIRs): 1) erbium-doped fibre amplifier (EDFA) and 2) second-order bidirectional Raman pumped amplification. The experiment is performed over different span lengths, demonstrating that, for an AIR of 6.8 bit/s/Hz, the Raman system enables an increase of 93 km (36 %) in span length. Further, at these distances, MC-DBP gives an improvement in AIR of 1 bit/s/Hz (to 7.8 bit/s/Hz) for both amplification schemes. The theoretical AIR gains for Raman and MC-DBP are shown to be preserved when considering low-density parity-check codes. Additionally, MC-DBP algorithms for both amplification schemes are compared in terms of performance and computational complexity. It is shown that to achieve the maximum MC-DBP gain, the Raman system requires approximately four times the computational complexity due to the distributed impact of fibre nonlinearity.