Edge-enhanced disruptive camouflage impairs shape discrimination

Disruptive colouration (DC) is a form of camouflage comprised of areas of pigmentation across a target’s surface that form false edges, which are said to impede detection by disguising the outline of the target. In nature, many species with DC also exhibit edge enhancement (EE); light areas have lighter edges and dark areas have darker edges. EE DC has been shown to undermine not only localisation but also identification of targets, even when they are not hidden (Sharman, Moncrieff, & Lovell, 2018). We use a novel task, where participants judge which “snake” is more “wiggly,” to measure shape discrimination performance for three colourations (uniform, DC, and EE DC) and two backgrounds (leafy and uniform). We show that EE DC impairs shape discrimination even when targets are not hidden in a textured background. We suggest that this mechanism may contribute to misidentification of EE DC targets

Astronomical image processing based on fractional calculus: the AstroFracTool

The implementation of fractional differential calculations can give new possibilities for image processing tools, in particular for those that are devoted to astronomical images analysis. As discussed in arxiv:0910.2381, the fractional differentiation is able to enhance the quality of images, with interesting effects in edge detection and image restoration. Here, we propose the AstroFracTool, developed to provide a simple yet powerful enhancement tool-set for astronomical images. This tool works evaluating the fractional gradient of an image map. It can help produce an output image useful for further research and scientific purposes, such as the detection of faint objects and galaxy structures, or, in the case of planetary studies, the enhancement of surface details.Comment: Keywords: Fractional calculation, image processing, astronom

Quantification of sub-resolution porosity in carbonate rocks by applying high-salinity contrast brine using X-ray microtomography differential imaging

Characterisation of the pore space in carbonate reservoirs and aquifers is of utmost importance in a number of applications such as enhanced oil recovery, geological carbon storage and contaminant transport. We present a new experimental methodology that uses high-salinity contrast brine and differential imaging acquired by X-ray tomography to non-invasively obtain three-dimensional spatially resolved information on porosity and connectivity of two rock samples, Portland and Estaillades limestones, including sub-resolution micro-porosity. We demonstrate that by injecting 30 wt% KI brine solution, a sufficiently high phase contrast can be achieved allowing accurate three-phase segmentation based on differential imaging. This results in spatially resolved maps of the solid grain phase, sub-resolution micro-pores within the grains, and macro-pores. The total porosity values from the three-phase segmentation for two carbonate rock samples are shown to be in good agreement with Helium porosity measurements. Furthermore, our flow-based method allows for an accurate estimate of pore connectivity and a distribution of porosity within the sub-resolution pores

Optimising Spatial and Tonal Data for PDE-based Inpainting

Some recent methods for lossy signal and image compression store only a few selected pixels and fill in the missing structures by inpainting with a partial differential equation (PDE). Suitable operators include the Laplacian, the biharmonic operator, and edge-enhancing anisotropic diffusion (EED). The quality of such approaches depends substantially on the selection of the data that is kept. Optimising this data in the domain and codomain gives rise to challenging mathematical problems that shall be addressed in our work. In the 1D case, we prove results that provide insights into the difficulty of this problem, and we give evidence that a splitting into spatial and tonal (i.e. function value) optimisation does hardly deteriorate the results. In the 2D setting, we present generic algorithms that achieve a high reconstruction quality even if the specified data is very sparse. To optimise the spatial data, we use a probabilistic sparsification, followed by a nonlocal pixel exchange that avoids getting trapped in bad local optima. After this spatial optimisation we perform a tonal optimisation that modifies the function values in order to reduce the global reconstruction error. For homogeneous diffusion inpainting, this comes down to a least squares problem for which we prove that it has a unique solution. We demonstrate that it can be found efficiently with a gradient descent approach that is accelerated with fast explicit diffusion (FED) cycles. Our framework allows to specify the desired density of the inpainting mask a priori. Moreover, is more generic than other data optimisation approaches for the sparse inpainting problem, since it can also be extended to nonlinear inpainting operators such as EED. This is exploited to achieve reconstructions with state-of-the-art quality. We also give an extensive literature survey on PDE-based image compression methods

Functional aspects of root architecture and mycorrhizal inoculation with respect to nutrient uptake capacity

ACESSO via B-on: http://dx.doi.org/10.1007/s00572-003-0254-5The aim of this research was to investigate theeffect of arbuscular mycorrhizal (AM) colonisation onroot morphology and nitrogen uptake capacity of carob(Ceratonia siliqua L.) under high and low nutrientconditions. The experimental design was a factorialarrangement of presence/absence of mycorrhizal fungusinoculation (Glomus intraradices) and high/low nutrientstatus. Percent AM colonisation, nitrate and ammoniumuptake capacity, and nitrogen and phosphorus contentswere determined in 3-month-old seedlings. Grayscale andcolour images were used to study root morphology andtopology, and to assess the relation between rootpigmentation and physiological activities. AM colonisationlead to a higher allocation of biomass to white andyellow parts of the root. Inorganic nitrogen uptakecapacity per unit root length and nitrogen content weregreatest in AM colonised plants grown under low nutrientconditions. A better match was found between plantnitrogen content and biomass accumulation, than betweenplant phosphorus content and biomass accumulation. It issuggested that the increase in nutrient uptake capacity ofAM colonised roots is dependent both on changes in rootmorphology and physiological uptake potential. Thisstudy contributes to an understanding of the role of AMfungi and root morphology in plant nutrient uptake andshows that AM colonisation improves the nitrogennutrition of plants, mainly when growing at low levelsof nutrients

Enhancement of dronogram aid to visual interpretation of target objects via intuitionistic fuzzy hesitant sets

In this paper, we address the hesitant information in enhancement task often caused by differences in image contrast. Enhancement approaches generally use certain filters which generate artifacts or are unable to recover all the objects details in images. Typically, the contrast of an image quantifies a unique ratio between the amounts of black and white through a single pixel. However, contrast is better represented by a group of pix- els. We have proposed a novel image enhancement scheme based on intuitionistic hesi- tant fuzzy sets (IHFSs) for drone images (dronogram) to facilitate better interpretations of target objects. First, a given dronogram is divided into foreground and background areas based on an estimated threshold from which the proposed model measures the amount of black/white intensity levels. Next, we fuzzify both of them and determine the hesitant score indicated by the distance between the two areas for each point in the fuzzy plane. Finally, a hyperbolic operator is adopted for each membership grade to improve the pho- tographic quality leading to enhanced results via defuzzification. The proposed method is tested on a large drone image database. Results demonstrate better contrast enhancement, improved visual quality, and better recognition compared to the state-of-the-art methods.Web of Science500866