Spectral Retinal Images Reconstruction
Nguyen, Uyen (2016)
Diplomityö
Nguyen, Uyen
2016
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2016052412727
https://urn.fi/URN:NBN:fi-fe2016052412727
Tiivistelmä
While red-green-blue (RGB) image of retina has quite limited information, retinal multispectral images provide both spatial and spectral information which could enhance the capability of exploring the eye-related problems in their early stages. In this thesis, two learning-based algorithms for reconstructing of spectral retinal images from the RGB images are developed by a two-step manner. First, related previous techniques are reviewed and studied. Then, the most suitable methods are enhanced and combined to have new algorithms for the reconstruction of spectral retinal images. The proposed approaches are based on radial basis function network to learn a mapping from tristimulus colour space to multi-spectral space. The resemblance level of reproduced spectral images and original images is estimated using spectral distance metrics spectral angle mapper, spectral correlation mapper, and spectral information divergence, which show a promising result from the suggested algorithms.