The study of mutual entropy (information) and capacity in classical system was extensively done after Shannon by several authors like Kolmogorov [12] and Gelfand [7]. In quantum systems, there have been several definitions of the mutual entropy for classical input and quantum output [5, 8, 9, 14]. In 1983, the author defined [21] the fully quantum mechanical mutual entropy by means of the relat...

A dispersive medium becomes entangled with zero-point fluctuations in the vacuum. We consider an arbitrary array of material bodies weakly interacting with a quantum field and compute the quantum mutual information between them. It is shown that the mutual information in D dimensions can be mapped to classical thermodynamic entropy in D+1 dimensions. As a specific example, we compute the mutual...

While studying complex systems, one of the fundamental questions is to identify causal relationships (i. e. which system drives which) between relevant subsystems. In this paper, we focus on informationtheoretic approaches for causality detection by means of directionality index based on mutual information estimation. We briefly review the current methods for mutual information estimation from ...

Non-negative point-wise priors such as saliency map, defocus field, foreground mask, object location window, and user given seeds, appear in many fundamental computer vision problems. These priors come in the form of confidence or probability values, and they are often incomplete, irregular, and noisy, which eventually makes the labelling task a challenge. Our goal is to extract image regions t...

Fusion of anatomic information in computed tomography (CT) and functional information in 18F-FDG positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined 18F-FDG PET/CT scanner, the two acquisitions are scanned separately an...

In this report a systematic approach is used to determine the approximate genetic network and robust dependencies underlying differentiation. The data considered is in the form of a binary matrix and represent the expression of the nine genes across the 99 colonies. The report is divided into two parts: the first part identifies significant pair-wise dependencies from the given binary matrix us...

We present a Gaussain model based approach for robust and automatic extraction of roads from very lowresolution satellite imagery. First, the input image is ltered to suppress the regions that the likelihood of existing a road pixel is low. Then, the road magnitude and orientation are computed by evaluating the responses from a quadruple orthogonal line lter set. A mapping from the line domain ...