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Morphology for Image Processing. Part I

Hiroshi Yamazaki, Czesław Byliński, Katsumi Wasaki (2012)

Formalized Mathematics

In this article we defined mathematical morphology image processing with set operations. First, we defined Minkowski set operations and proved their properties. Next, we defined basic image processing, dilation and erosion proving basic fact about them [5], [8].

MRA super-wavelets.

Bildea, Stefan, Dutkay, Dorin Ervin, Picioroaga, Gabriel (2005)

The New York Journal of Mathematics [electronic only]

Multichannel deblurring of digital images

Michal Šorel, Filip Šroubek, Jan Flusser (2011)

Kybernetika

Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of...

Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy

Hoai Linh Tran, Van Nam Pham, Hoang Nam Vuong (2014)

International Journal of Applied Mathematics and Computer Science

The paper presents a new system for ECG (ElectroCardioGraphy) signal recognition using different neural classifiers and a binary decision tree to provide one more processing stage to give the final recognition result. As the base classifiers, the three classical neural models, i.e., the MLP (Multi Layer Perceptron), modified TSK (Takagi-Sugeno-Kang) and the SVM (Support Vector Machine), will be applied. The coefficients in ECG signal decomposition using Hermite basis functions and the peak-to-peak...

Multi-variate correlation and mixtures of product measures

Tim Austin (2020)

Kybernetika

Total correlation (‘TC’) and dual total correlation (‘DTC’) are two classical ways to quantify the correlation among an n -tuple of random variables. They both reduce to mutual information when n = 2 . The first part of this paper sets up the theory of TC and DTC for general random variables, not necessarily finite-valued. This generality has not been exposed in the literature before. The second part considers the structural implications when a joint distribution μ has small TC or DTC. If TC ( μ ) = o ( n ) , then μ is...

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