@inproceedings{01ef8c119316479b8367b70cfbba716d,
title = "Integration of contextual knowledge in unsupervised sub-pixel classification",
abstract = "In this paper, we investigate the use of coarse image features for predicting class label distributions at a finer scale. The major contributions of this work are 1) use of coarse image features to improve the optimization formulation of conventional rank based approaches 2) use of inter class compatibility information from coarse images to refine the predicted target distribution 3) an enhanced unsupervised variogram based sub-pixel mapping approach 4) inclusion of abundance estimation uncertainty in the unmixing process. The proposed modifications on rank based and variogram based approaches have produced an accuracy improvement of 10-15%. The sensitivities of these approaches towards tunable parameters are also analyzed.",
keywords = "Context, Sub-pixel mapping, Variogram",
author = "Arun, {P. V.} and Buddhiraju, {Krishna Mohan} and Alok Porwal",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016 ; Conference date: 21-08-2016 Through 24-08-2016",
year = "2016",
month = jun,
day = "28",
doi = "10.1109/WHISPERS.2016.8071663",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "Institute of Electrical and Electronics Engineers",
booktitle = "2016 8th Workshop on Hyperspectral Image and Signal Processing",
address = "United States",
}