8,737 research outputs found
Noise estimation in infrared image sequences: a tool for the quantitative evaluation of the effectiveness of registration algorithms
Quantum Bayesian methods and subsequent measurements
After a derivation of the quantum Bayes theorem, and a discussion of the
reconstruction of the unknown state of identical spin systems by repeated
measurements, the main part of this paper treats the problem of determining the
unknown phase difference of two coherent sources by photon measurements. While
the approach of this paper is based on computing correlations of actual
measurements (photon detections), it is possible to derive indirectly a
probability distribution for the phase difference. In this approach, the
quantum phase is not an observable, but a parameter of an unknown quantum
state. Photon measurements determine a probability distribution for the phase
difference. The approach used in this paper takes into account both photon
statistics and the finite efficiency of the detectors.Comment: Expanded and corrected version. 13 pages, 1 figur
Evaluation of time-series registration methods in dynamic area telethermometry for breast cancer detection
Automated motion reduction in 3D dynamic infrared imaging is on demand in many applications. Few methods for registering time-series dynamic infrared frames have been proposed. Almost all such methods are feature based algorithms requiring manual intervention. We apply different automated registration methods based on spatial displacement to 11 datasets of Breast Dynamic Infrared Imaging (DIRI) and evaluate the results in terms of both the image similarity and anatomical consistency of the transformation. The aim is to optimize the registration strategy for breast DIRI in order to improve the spectral analysis of temperature modulation; thus facilitating the acquisition procedure in a Dynamic Area Telethermometry framework. The results show that symmetric diffeomorphic demons registration outperforms both warped frames similarity and smoothness of deformation fields; hence proving effective for time-series dynamic infrared registratio
Scale-free network growth by ranking
Network growth is currently explained through mechanisms that rely on node
prestige measures, such as degree or fitness. In many real networks those who
create and connect nodes do not know the prestige values of existing nodes, but
only their ranking by prestige. We propose a criterion of network growth that
explicitly relies on the ranking of the nodes according to any prestige
measure, be it topological or not. The resulting network has a scale-free
degree distribution when the probability to link a target node is any power law
function of its rank, even when one has only partial information of node ranks.
Our criterion may explain the frequency and robustness of scale-free degree
distributions in real networks, as illustrated by the special case of the Web
graph.Comment: 4 pages, 2 figures. We extended the model to account for ranking by
arbitrarily distributed fitness. Final version to appear on Physical Review
Letter
Degradability of Bosonic Gaussian channels
The notion of weak-degradability of quantum channels is introduced by
generalizing the degradability definition given by Devetak and Shor. Exploiting
the unitary equivalence with beam-splitter/amplifier channels we then prove
that a large class of one-mode Bosonic Gaussian channels are either weakly
degradable or anti-degradable. In the latter case this implies that their
quantum capacity Q is null. In the former case instead, this allows us to
establish the additivity of the coherent information for those maps which admit
unitary representation with single-mode pure environment.Comment: 7 pages, 1 figure, 1 table (minor editing
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