775 resultados para spatiotemporal entropic thresholding


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Tayrona National Natural Park (TNNP; 11°17' - 11°22' N and 73°53' - 74°12' W) is a hotspot of coral reef biodiversity in the Colombian Caribbean, located between the city of Santa Marta (>455,000 inhabitants) and several smaller river mouths (Rio Piedras, Mendihuaca, Guachaca). The region experiences a strong seasonal variation in physical parameters (temperature, salinity, wind, and water currents) due to alternating dry seasons with coastal upwelling and rainy seasons. Here, a range of water quality parameters relevant for coral reef functioning is provided. Water quality was measured directly above local coral reefs (~10 m water depth) by a monthly monitoring for up to 25 months in the four TNNP bays (Chengue, Gayraca, Neguanje, and Cinto) and at sites with different degree of exposition to winds, waves and water currents (exposed vs. sheltered sites) within each bay. The water quality parameters include: inorganic nutrient (nitrate, nitrite and soluble reactive phosphorus), chlorophyll a, particulate organic carbon and nitrogen concentrations (with a replication of n=3) as well as oxygen availability, biological oxygen demand, seawater pH, and water clarity (with a replication of n=4). This is by far the most comprehensive coral reefs water quality dataset for the region. A detailed description of the methods can be found within the referenced publications.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.

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Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on several factors being one of them surface micro-topography, usually quanti[U+FB01]ed trough soil surface roughness (SSR). SSR greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. The methods commonly used to measure SSR involve measuring point elevation using a pin roughness meter or laser, both of which are labor intensive and expensive. Lately a simple and inexpensive technique based on percentage of shadow in soil surface image has been developed to determine SSR in the field in order to obtain measurement for wide spread application. One of the first steps in this technique is image de-noising and thresholding to estimate the percentage of black pixels in the studied area. In this work, a series of soil surface images have been analyzed applying several de-noising wavelet analysis and thresholding algorithms to study the variation in percentage of shadows and the shadows size distribution

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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

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We have determined the cross-section σ for color center generation under single Br ion impacts on amorphous SiO2. The evolution of the cross-sections, σ(E) and σ(Se), show an initial flat stage that we associate to atomic collision mechanisms. Above a certain threshold value (Se > 2 keV/nm), roughly coinciding with that reported for the onset of macroscopic disorder (compaction), σ shows a marked increase due to electronic processes. In this regime, a energetic cost of around 7.5 keV is necessary to create a non bridging oxygen hole center-E′ (NBOHC/E′) pair, whatever the input energy. The data appear consistent with a non-radiative decay of self-trapped excitons.

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A novel class of graphs, here named quasiperiodic, are const ructed via application of the Horizontal Visibility algorithm to the time series generated along the quasiperiodic route to chaos. We show how the hierarchy of mode-locked regions represented by the Far ey tree is inherited by their associated graphs. We are able to establish, via Renormalization Group (RG) theory, the architecture of the quasiperiodic graphs produced by irrational winding numbers with pure periodic continued fraction. And finally, we demonstrate that the RG fixed-point degree distributions are recovered via optimization of a suitably defined graph entropy

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Electronic devices endowed with camera platforms require new and powerful machine vision applications, which commonly include moving object detection strategies. To obtain high-quality results, the most recent strategies estimate nonparametrically background and foreground models and combine them by means of a Bayesian classifier. However, typical classifiers are limited by the use of constant prior values and they do not allow the inclusion of additional spatiodependent prior information. In this Letter, we propose an alternative Bayesian classifier that, unlike those reported before, allows the use of additional prior information obtained from any source and depending on the spatial position of each pixel.