@inproceedings{
 title = {Fovea Window for Wavelet-based Compression},
 type = {inproceedings},
 year = {2011},
 keywords = {Data compression,Discrete cosine transforms,Discrete wavelet transforms,Image processing},
 pages = {661-672},
 volume = {152 LNEE},
 websites = {http://link.springer.com/10.1007/978-1-4614-3535-8_55},
 publisher = {Springer},
 id = {bf0fa016-5f7e-3a10-941f-edf6223d81e3},
 created = {2022-08-29T17:43:05.035Z},
 file_attached = {false},
 profile_id = {940dd160-7d67-3a5f-b9f8-935da0571367},
 group_id = {92fccab2-8d44-33bc-b301-7b94bb18523c},
 last_modified = {2022-08-29T17:43:05.035Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 source_type = {CONF},
 private_publication = {false},
 abstract = {Wavelet foveated compression can be used in real-time video processing frameworks for reducing the communication overhead while keeping high visual quality. Such algorithm leads into high rate compression results due to the fact that the information loss is isolated outside a region of interest (ROI). The fovea compression can also be applied to other classic transforms such as the commonly used the discrete cosine transform (DCT). In this paper, a fovea window for wavelet-based compression is proposed. The proposed window allows isolate a fovea region over an image. A comparative analysis has been performed showing different error and compression rates between the proposed fovea window for wavelet-based and the DCT-based compression algorithms. Simulation results show that with foveated compression high ratio of compression can be achieved while keeping high quality over the designed ROI. © 2013 Springer Science+Business Media.},
 bibtype = {inproceedings},
 author = {Galan-Hernandez, J. C. and Alarcon-Aquino, V. and Starostenko, O. and Ramirez-Cortes, J. M.},
 doi = {10.1007/978-1-4614-3535-8_55},
 booktitle = {Lecture Notes in Electrical Engineering}
}

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