INTRODUCTION Mathematical morphology offers some powerful tools for the image interpolation. The idea of the application of mathematical morphology to the image interpolation has been introduced in 1994 in the Center of Mathematical Morphology of Paris School of Mines. The basics of the morphological interpolation methods and the majority of the interpolation algorithms was developed by J.Serra...

Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...

The work compares the of sparse image interpolation methods such as: - method sequential computation Fourier spectrum (IMSCS), projections onto convex sets (projections sets, POCS), and amplitude iterations (MAI). All calculations necessary for reconstruction images are performed only on spatial spectra. As an example, aerospace digital is used, which typical tasks remote sensing earth's surfac...

Climate plays a key role in ecosystem services. Understanding microclimate change can be significant help making the right decision for ecosystems and buffering effects of global warming. Given large distances between meteorological stations changes climate variables within short distances, such variations cannot detected just by using observed data. This study aimed at determining spatial stru...

Introduction: To estimate the accuracy levels of Lagrange, Newton backward interpolation, and linear interpolation methods in estimating the output factors for square fields used in linear accelerator for 6 MV photons at various depths. Materials and Methods: Ionization measurements were carried out in radiation field analyzer in linear accelerator for 6 MV beams at the depths of 5 and 10 cm by...