Automatic enhancement of noisy image sequences through local spatio-temporal spectrum analysis

Contiene: 13 ilustraciones, 2 tablas y fórmulasA fully automatic method is proposed to produce an enhanced image from a very noisy sequence consisting of a translating object over a background with different translation motion. The method is based on averaging registered versions of the frames in which the object has been motion compensated. Conventional techniques for displacement estimation are not adequate for these very noise sequences, and thus a new strategy has been used taking advantage of the simple model of the sequences. First, the local spatio-temporal spectrum is estimated through a bank of multidirectional/multiscale third order Gaussian derivative filters, yielding a representation of the sequence that facilitates further processing and analysis tasks. Then, energy-related measurements describing the local texture and motion are easily extracted from this representation. These descriptors are used to segment the sequence based on a local joint measure of motion and texture. Once the object of interest has been segmented, its velocity is estimated applying the gradient constraint to the output of a directional band-pass filter for all pixels belonging to the object. Velocity estimates are then used to compensate the motion prior to the average. The results obtained with real sequences of moving ships taken under very noisy conditions are highly satisfactory, demonstrating the robustness and usefulness of the proposed method.Supported by the Comisión Interministerial de Ciencia y Tecnología of Spain, grant TIC98-0925-C02-01Peer reviewe

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Image enhancement techniques applied to solar feature detection

This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical union of directional filtering results, the remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed techniques can achieve excellent results in detecting large filaments and good detection rates for small filaments. The final chapter discusses proposed directions of the future research and applications to other areas of solar image processing, in particular to detection of solar flares, plages and sunspots

Engineering Photon Sources for Practical Quantum Information Processing:If you liked it then you should have put a ring on it

Integrated quantum photonics offers a promising route to the realisation of universal fault-tolerant quantum computers. Much progress has been made on the theoretical aspects of a future quantum information processor, reducing both error thresholds and circuit complexity. Currently, engineering efforts are focused on integrating the most valuable technologies for a photonic quantum computer; pure single-photon sources, low-loss phase shifters and passivecircuit components, as well as efficient single-photon detectors and corresponding electronics.Here, we present efforts to target the former under the constraints imposed by the latter. We engineer the spectral correlations of photons produced by a heralded single-photon source, such that they produce photons in pure quantum states (99.1±0.1 % purity), and enable additional optimisation using temporal shaping of the pump field. Our source also has a high intrinsicheralding efficiency (94.0 ± 2.9 %) and produces photon pairs at a rate (4.4 ± 0.1 MHz mW−2) which is an order of magnitude better than previously predicted by the literature for a resonant source of this purity. Additionally, we present tomographic methodologies that fully describe the photonic quantum states that we produce, without the use of analytical models, and as a means of verifying the quantum states we create, entitled – "Quantum-referenced SpontaneousEmission Tomography" (Q-SpET). We also design reconfigurable photonic circuits that can be operated at cryogenic temperatures, with zero static power consumption, entitled – "Cladding Layer Manipulation" (CLM). These devices function as on-chip phase shifters, enabling the local reconfiguration of circuit elements using established technologies but removing the need for active power consumption to maintain the reconfigured circuit. These devices are capable ofan Lπ = 12.3 ± 0.3 µm, a ∼7x reduction in length when compared to the thermo-optic phaseshifters used throughout this thesis. Finally, we investigate how pure photon sources operate as part of larger circuits within the typical design rules of photonic quantum circuits. Using this information to accurately model all of the spurious contributions to the final photonic quantumstate, which we call a form of nonlinear noise. This noise can decrease source purity to below 40 %, significantly affecting the fidelity of Hong-Ou-Mandel interference, and subsequently, our ability to reliably create fundamental resources for photonic quantum computers. All of this contributes to our design of a fundamental building block for integrated quantum photonic processors, the functionality of which can be predicted at scale, under the conditions imposed by the rest of the processor

Concurrent fNIRS and EEG for brain function investigation: A systematic, methodology-focused review

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research

LUCI onboard Lagrange, the Next Generation of EUV Space Weather Monitoring

LUCI (Lagrange eUv Coronal Imager) is a solar imager in the Extreme UltraViolet (EUV) that is being developed as part of the Lagrange mission, a mission designed to be positioned at the L5 Lagrangian point to monitor space weather from its source on the Sun, through the heliosphere, to the Earth. LUCI will use an off-axis two mirror design equipped with an EUV enhanced active pixel sensor. This type of detector has advantages that promise to be very beneficial for monitoring the source of space weather in the EUV. LUCI will also have a novel off-axis wide field-of-view, designed to observe the solar disk, the lower corona, and the extended solar atmosphere close to the Sun-Earth line. LUCI will provide solar coronal images at a 2-3 minute cadence in a pass-band centred on 19.5 nm. Observations made through this pass-band allow for the detection and monitoring of semi-static coronal structures such as coronal holes, prominences, and active regions; as well as transient phenomena such as solar flares, limb Coronal Mass Ejections (CMEs), EUV waves, and coronal dimmings. The LUCI data will complement EUV solar observations provided by instruments located along the Sun-Earth line such as PROBA2-SWAP, SUVI-GOES and SDO-AIA, as well as provide unique observations to improve space weather forecasts. Together with a suite of other remote-sensing and in-situ instruments onboard Lagrange, LUCI will provide science quality operational observations for space weather monitoring