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Modern techniques treat color images as separate monochrome images for processing.Partly, because there is no straightforward generalization of linear filters available for color. However the algorithms yield more accurate results when the correlation among color bands are exploited which shows fundamental difference to process the color images. Earlier work [8] reported the transformation of the color images using Quaternion Fourier Transforms and the realization of a holistic filter based on Quaternion convolution. Here, we discuss the rotor based convolution techniques, a generalization of the previous work, within a new mathematical framework in Geometric Algebra. Based thereupon, a novel hardware architecture is proposed. Experiments show the edge detection with this technique belong to a class of linear vector filter and is holistic in nature. It is tailored for image processing applications, providing an acceptable application performance requirements. The usefulness of the introduced approach was demonstrated by analyzing and implementing a computation intensive edge detection algorithm on this hardware.

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Theoretical predictions as well as experiments performed at storage rings have shown that the lifetimes of β-radionuclides can change significantly as a function of the ionization state. In this paper we describe an innovative approach, based on the use of a compact plasma trap to emulate selected stellar-like conditions. It has been proposed within the PANDORA project (Plasmas for Astrophysics, Nuclear Decay Observation and Radiation for Archaeometry) with the aim to measure, for the first time in plasma, nuclear β-decay rates of radionuclides involved in nuclear-astrophysics processes. To achieve this task, a compact magnetic plasma trap has been designed to reach the needed plasma densities, temperatures, and charge-states distributions. A multi-diagnostic setup will monitor, on-line, the plasma parameters, which will be correlated with the decay rate of the radionuclides. The latter will be measured through the detection of the γ-rays emitted by the excited daughter nuclei following the β-decay. An array of 14 HPGe detectors placed around the trap will be used to detect the emitted γ-rays. For the first experimental campaign three isotopes, 176Lu, 134Cs, and 94Nb, were selected as possible physics cases. The newly designed plasma trap will also represent a tool of choice to measure the plasma opacities in a broad spectrum of plasma conditions, experimentally poorly known but that have a great impact on the energy transport and spectroscopic observations of many astrophysical objects. Status and perspectives of the project will be highlighted in the paper.

Aim of the PANDORA (Plasmas for Astrophysics, Nuclear Decays Observation and Radiation for Archeometry) project is the in-plasma measurements of decay rates of beta radionuclides as a function of the ionization stage. In this view, a precise calculation of plasma electrons density and energy is mandatory, being responsible for ions’ creations and their spatial distribution following plasma neutrality. This paper describes the results of the INFN simulation tools applied for the first time to the PANDORA plasma, including electromagnetic calculations and electrons’ dynamics within the so-called self-consistent loop. The distribution of the various electrons’ population will be shown, with special attention to the warm component on which depends the obtained ions’ charge state distribution. The strict relation of the results with the evaluation of the in-plasma nuclear decays will be also explained.

The PANDORA project aims to investigate, by a new experimental approach, the β-decays lifetimes of isotopes of nuclear astrophysics interest as a function of thermodynamic conditions of a laboratory plasma able to mimic some stellar-like conditions. A γ-ray detection system was designed by GEANT4 simulations to tag the in-plasma β-decays via the γ-rays emitted from the excited states of the daughter nuclei. The feasibility of PANDORA, in terms of significance levels, was checked by a “virtual experiment run”, also investigating the sensitivity for discriminating among different theoretical predictions.