Image Superresolution via Divergence Matrix and Automatic Detection of Crossover

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Dmytro Peleshko 1,* Taras Rak 2 Ivan Izonin 1

1. Lviv Polytechnic National University / Department of Publishing Information Technologies, Lviv, 79013, Ukraine

2. Lviv State University of Life Safety, Lviv, 79013, Ukraine

* Corresponding author.


Received: 11 Feb. 2016 / Revised: 17 Jun. 2016 / Accepted: 5 Sep. 2016 / Published: 8 Dec. 2016

Index Terms

Superresolution, similarity measure, crossover operations, automatic detection, aggregate divergence matrix


The paper describes the image superresolution method with aggregate divergence matrix and automatic detection of crossover. Formulation of the problem, building extreme optimization task and its solution for solving the automation determination of the crossover coefficient is presented. Different ways for building oversampling images algorithms based on the proposed method are shows. Based on practical experiments shows the effectiveness of the procedure of automatically the determination of the crossover coefficient. Experimentally established the effectiveness of the procedures oversampling images at high zoom resolution by the developed method.

Cite This Paper

Dmytro Peleshko, Taras Rak, Ivan Izonin, "Image Superresolution via Divergence Matrix and Automatic Detection of Crossover", International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.12, pp.1-8, 2016. DOI:10.5815/ijisa.2016.12.01


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