@inproceedings{066c6b85f28a4f9c88630ea55bed25ec,
title = "Tensor completion for on-board compression of hyperspectral images",
abstract = "We present a new image compression scheme for hyperspectral images based on the newly-emerged matrix/tensor completion theory. Unlike typical transform-coding based methods, the proposed approach does not require any transform to be performed by the imaging sensor when doing on-board compression. Only a small set of pixels on a sparse set of locations on the imaging sensor needs to be captured and transmitted for each image. The decoder side relies on matrix/tensor completion for reconstructing the original images. Hence the scheme can drastically reduce the computation and bandwidth requirements on the on-board imaging sensors. Experiments show that the proposed method is able to obtain compression performance close to JPEG2000 while enjoying the afore-mentioned unique benefits.",
keywords = "Hyperspectral image compression, Matrix completion, Tensor completion",
author = "Nan Li and Baoxin Li",
year = "2010",
doi = "10.1109/ICIP.2010.5651225",
language = "English (US)",
isbn = "9781424479948",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "517--520",
booktitle = "2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings",
note = "2010 17th IEEE International Conference on Image Processing, ICIP 2010 ; Conference date: 26-09-2010 Through 29-09-2010",
}