0000000000975172

AUTHOR

Matti Eskelinen

showing 3 related works from this author

Dangers of Demosaicing : Confusion From Correlation

2019

Images from colour sensors using Bayer filter arrays require demosaicing before viewing or further analysis. Advanced demosaicing methods use empirical knowledge of inter-channel correlations to reduce interpolation artefacts in the resulting images. These inter-channel correlations are however different for standard RGB cameras and hyperspectral imagers using colour sensors with added narrow-band spectral filtering. We study the effects of conventional demosaicing methods on hyperspectral images with a dataset originally collected without a colour filter array. We find that using advanced methods instead of bilinear interpolation results in an overall increase of 9–14 % in absolute error a…

colour sensorskuvantaminenspektrikuvaushyperspectral imagershyperspektrikuvantaminen
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Koulujen ja yritysten välinen yhteistyö : opettajien kokemuksia ja ajatuksia

2000

mainontayrittäjyyskasvatusmarkkinointisponsorointiyritysyhteistyökuluttajakasvatus
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Software Framework for Hyperspectral Data Exploration and Processing in MATLAB

2017

This paper presents a user introduction and a general overview of the MATLAB software package hsicube developed by the author for simplifying the data manipulation and visualization tasks often encountered in hyperspectral analysis work, and the design principles and software development methods used by the author. The framework implements methods for slicing, masking, visualization and application of existing functions to hyperspectral data cubes without the need to use explicit indexing or reshaping, as well as enabling expressive syntax for combining these operations on the command line for highly efficient data analysis workflows. It also includes utilities for interfacing with existing…

MATLABsoftwarehyperspectral imagingdata exploration
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