The Research of Granular Computing Applied in Image Mosaic

Based on the existing image mosaic technology, this paper introduces the granular computing and obtains a simplified new algorithm. The image mosaic executed by this algorithm at first establishes correlation model on the basis of granular computing theory, and obtains edge map of each image needing mosaic. The new calculation method is used to calculate gradient of in different columns of edge map, to obtain the feature point coordinates with the maximum gradient; meanwhile, all feature points of two images are matched with each other, to acquire the best matching point. In addition, the error-correcting mechanism is introduced in the matching process, which is used to delete feature points with matching error. The correlation calculation is carried out for the matching pixels acquired by the above processing, to get the feature transformational matrix of the two images. According to the matrix, two separated image maps map into the same plane. The slow transitional mosaic method is applied in the aspect of image addition plus overlap removal, so that images have no bulgy boundary after mosaics. The whole image mosaic process shows that the given granular computing algorithm is superior to the traditional one both in the number of processed images and the number of processing, and the mosaic image gained has high quality

Proper Motions of Sunspots' Umbral Dots at High Temporal and Spatial Resolution

To deepen the analysis of the photometric properties of the umbra of a sunspot, we study proper motions of small features such as umbral dots (UDs) inside a single sunspot observed by the Solar Optical Telescope of Hinode close to the disk center. We consider horizontal flows with high precision and details to study the transient motion behavior of UDs in short time intervals. Blue continuum images were first deconvolved with the point-spread function, such that the stray light is precisely removed and the original resolution is improved. Several images were co-added to improve the signal-to-noise ratio, keeping a reasonable temporal resolution and checking that the results are reproducible. The Fourier local correlation tracking technique is applied to the new corrected time sequence of images, and horizontal velocity maps were obtained both for the whole umbra and for a high-resolution small region of the umbra to study the smallest details of the velocity fields. We used two different Gaussian tracking windows (0.8arcsec and 0.2arcsec), which reveals two types of horizontal motions for umbral features. First, a global inner penumbra and peripheral umbra inward motion directed to the central parts is revealed as an overall proper motion of bright peripheral fine structures. Second, motions matching small cells inside the darkest parts of the umbra with apparent sink and source areas are revealed, suggesting possible upflows and downflows appearing in different bright and dark locations without a definite answer regarding their brightness identification with a convective or a buoyant cell

Mitigating the effect of covariates in face recognition

Current face recognition systems capture faces of cooperative individuals in controlled environment as part of the face recognition process. It is therefore possible to control lighting, pose, background, and quality of images. However, in a real world application, we have to deal with both ideal and imperfect data. Performance of current face recognition systems is affected for such non-ideal and challenging cases. This research focuses on designing algorithms to mitigate the effect of covariates in face recognition.;To address the challenge of facial aging, an age transformation algorithm is proposed that registers two face images and minimizes the aging variations. Unlike the conventional method, the gallery face image is transformed with respect to the probe face image and facial features are extracted from the registered gallery and probe face images. The variations due to disguises cause change in visual perception, alter actual data, make pertinent facial information disappear, mask features to varying degrees, or introduce extraneous artifacts in the face image. To recognize face images with variations due to age progression and disguises, a granular face verification approach is designed which uses dynamic feed-forward neural architecture to extract 2D log polar Gabor phase features at different granularity levels. The granular levels provide non-disjoint spatial information which is combined using the proposed likelihood ratio based Support Vector Machine match score fusion algorithm. The face verification algorithm is validated using five face databases including the Notre Dame face database, FG-Net face database and three disguise face databases.;The information in visible spectrum images is compromised due to improper illumination whereas infrared images provide invariance to illumination and expression. A multispectral face image fusion algorithm is proposed to address the variations in illumination. The Support Vector Machine based image fusion algorithm learns the properties of the multispectral face images at different resolution and granularity levels to determine optimal information and combines them to generate a fused image. Experiments on the Equinox and Notre Dame multispectral face databases show that the proposed algorithm outperforms existing algorithms. We next propose a face mosaicing algorithm to address the challenge due to pose variations. The mosaicing algorithm generates a composite face image during enrollment using the evidence provided by frontal and semiprofile face images of an individual. Face mosaicing obviates the need to store multiple face templates representing multiple poses of a users face image. Experiments conducted on three different databases indicate that face mosaicing offers significant benefits by accounting for the pose variations that are commonly observed in face images.;Finally, the concept of online learning is introduced to address the problem of classifier re-training and update. A learning scheme for Support Vector Machine is designed to train the classifier in online mode. This enables the classifier to update the decision hyperplane in order to account for the newly enrolled subjects. On a heterogeneous near infrared face database, the case study using Principal Component Analysis and C2 feature algorithms shows that the proposed online classifier significantly improves the verification performance both in terms of accuracy and computational time

Towards the spatial resolution of metalloprotein charge states by detailed modeling of XFEL crystallographic diffraction.

Oxidation states of individual metal atoms within a metalloprotein can be assigned by examining X-ray absorption edges, which shift to higher energy for progressively more positive valence numbers. Indeed, X-ray crystallography is well suited for such a measurement, owing to its ability to spatially resolve the scattering contributions of individual metal atoms that have distinct electronic environments contributing to protein function. However, as the magnitude of the shift is quite small, about +2 eV per valence state for iron, it has only been possible to measure the effect when performed with monochromated X-ray sources at synchrotron facilities with energy resolutions in the range 2-3 × 10-4 (ΔE/E). This paper tests whether X-ray free-electron laser (XFEL) pulses, which have a broader bandpass (ΔE/E = 3 × 10-3) when used without a monochromator, might also be useful for such studies. The program nanoBragg is used to simulate serial femtosecond crystallography (SFX) diffraction images with sufficient granularity to model the XFEL spectrum, the crystal mosaicity and the wavelength-dependent anomalous scattering factors contributed by two differently charged iron centers in the 110-amino-acid protein, ferredoxin. Bayesian methods are then used to deduce, from the simulated data, the most likely X-ray absorption curves for each metal atom in the protein, which agree well with the curves chosen for the simulation. The data analysis relies critically on the ability to measure the incident spectrum for each pulse, and also on the nanoBragg simulator to predict the size, shape and intensity profile of Bragg spots based on an underlying physical model that includes the absorption curves, which are then modified to produce the best agreement with the simulated data. This inference methodology potentially enables the use of SFX diffraction for the study of metalloenzyme mechanisms and, in general, offers a more detailed approach to Bragg spot data reduction

Seismotectonic, structural, volcanologic, and geomorphic study of New Zealand; indigenous forest assessment in New Zealand; mapping, land use, and environmental studies in New Zealand, volume 2

The author has identified the following significant results. Ship detection via LANDSAT MSS data was demonstrated. In addition, information on ship size, orientation, and movement was obtained. Band 7 was used for the initial detection followed by confirmation on other MSS bands. Under low turbidity, as experienced in open seas, the detection of ships 100 m long was verified and detection of ships down to 30 m length theorized. High turbidity and sea state inhibit ship detection by decreasing S/N ratios. The radiance effect from snow of local slope angles and orientation was also studied. Higher radiance values and even overloading in three bands were recorded for the sun-facing slope. Local hot spots from solar reflection appear at several locations along transect D-C in Six Mile Creek Basin during September 1976

Here is now and there the sound of the land: ground-breaking

Scientific and Sonic Perceptions of the African Sahel: Societies are often required to react to extreme events that arise through either anthropogenic or natural processes. Such extremity might be measured is in terms of its immediacy and intensity; it demands comprehension against understood norms. For example, our present-day debate on future climatic change is driven by scientific assertion, reinforced by evidence gathered from both instrument and indirect proxy measurements, whilst the varying societal responses are predicated by everyday cultural experiences. In contrast, places considered to offer experiences at the boundaries of or outside the everyday, e.g. hot and cold deserts, provide a different conception of extreme. In this conception, change and the rates of change typically lack context, validation and position within everyday norms. Consequently, it is within such surroundings that the greatest tension occurs between the perception of place and rates of change. While the methodologies of science and art practice are often respectively considered positivistic and non-rational, both are in fact able to investigate the extreme in this context. Whether or not such characterisations are legitimate, the obvious epistemological differences both illuminate and problematise our understanding. In this paper we describe a real-time generative installation commissioned from the authors by the UK Research Councils called Ground-breaking: Extreme Landscapes in Grains and Pixels that attempts to explore and test these differences. Further examples are available at http://www.ground-breaking.net

Deconstructing the glass transition through critical experiments on colloids

The glass transition is the most enduring grand-challenge problem in contemporary condensed matter physics. Here, we review the contribution of colloid experiments to our understanding of this problem. First, we briefly outline the success of colloidal systems in yielding microscopic insights into a wide range of condensed matter phenomena. In the context of the glass transition, we demonstrate their utility in revealing the nature of spatial and temporal dynamical heterogeneity. We then discuss the evidence from colloid experiments in favor of various theories of glass formation that has accumulated over the last two decades. In the next section, we expound on the recent paradigm shift in colloid experiments from an exploratory approach to a critical one aimed at distinguishing between predictions of competing frameworks. We demonstrate how this critical approach is aided by the discovery of novel dynamical crossovers within the range accessible to colloid experiments. We also highlight the impact of alternate routes to glass formation such as random pinning, trajectory space phase transitions and replica coupling on current and future research on the glass transition. We conclude our review by listing some key open challenges in glass physics such as the comparison of growing static lengthscales and the preparation of ultrastable glasses, that can be addressed using colloid experiments.Comment: 137 pages, 45 figure

Plato's cube and the natural geometry of fragmentation

Plato envisioned Earth's building blocks as cubes, a shape rarely found in nature. The solar system is littered, however, with distorted polyhedra -- shards of rock and ice produced by ubiquitous fragmentation. We apply the theory of convex mosaics to show that the average geometry of natural 2D fragments, from mud cracks to Earth's tectonic plates, has two attractors: "Platonic" quadrangles and "Voronoi" hexagons. In 3D the Platonic attractor is dominant: remarkably, the average shape of natural rock fragments is cuboid. When viewed through the lens of convex mosaics, natural fragments are indeed geometric shadows of Plato's forms. Simulations show that generic binary breakup drives all mosaics toward the Platonic attractor, explaining the ubiquity of cuboid averages. Deviations from binary fracture produce more exotic patterns that are genetically linked to the formative stress field. We compute the universal pattern generator establishing this link, for 2D and 3D fragmentation.Comment: main: 6 pages, 6 figures, supplementary: 18 pages, 12 figure

Non-local thermodynamic equilibrium inversions from a 3D MHD chromospheric model

The structure of the solar chromosphere is believed to be governed by magnetic fields, even in quiet-Sun regions that have a relatively weak photospheric field. During the past decade inversion methods have emerged as powerful tools for analyzing the chromosphere of active regions. The applicability of inversions to infer the stratification of the physical conditions in a dynamic 3D solar chromosphere has not yet been studied in detail. This study aims to establish the diagnostic capabilities of non-local thermodynamical equilibrium (NLTE) inversion techniques of Stokes profiles induced by the Zeeman effect in the Ca II 8542 line. We computed the Ca II atomic level populations in a snapshot from a 3D radiation-MHD simulation of the quiet solar atmosphere in non-LTE using the 3D radiative transfer code Multi3d. These populations were used to compute synthetic full-Stokes profiles in the Ca II 8542 line using 1.5D radiative transfer and the inversion code Nicole. The profiles were then spectrally degraded to account for finite filter width and Gaussian noise was added to account for finite photon flux. These profiles were inverted using Nicole and the results were compared with the original model atmosphere. Our NLTE inversions applied to quiet-Sun synthetic observations provide reasonably good estimates of the chromospheric magnetic field, line-of-sight velocities and somewhat less accurate, but still very useful, estimates of the temperature. Three dimensional scattering of photons cause cool pockets in the chromosphere to be invisible in the line profile and consequently they are also not recovered by the inversions. To successfully detect Stokes linear polarization in this quiet snapshot, a noise level below 10^{-3.5} is necessary.Comment: Accepted for publication in Astronomy & Astrophysic