Distributed Image Compression for Sensor Networks using Correspondence Analysis and Super-Resolution
dc.citation.bibtexName | inproceedings | en_US |
dc.citation.conferenceName | IEEE International Conference on Image Processing | en_US |
dc.citation.location | Barcelona, Spain | en_US |
dc.contributor.author | Wagner, Raymond | en_US |
dc.contributor.author | Nowak, Robert David | en_US |
dc.contributor.author | Baraniuk, Richard G. | en_US |
dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
dc.date.accessioned | 2007-10-31T01:00:02Z | en_US |
dc.date.available | 2007-10-31T01:00:02Z | en_US |
dc.date.issued | 2003-09-01 | en_US |
dc.date.modified | 2006-07-19 | en_US |
dc.date.note | 2003-08-14 | en_US |
dc.date.submitted | 2003-09-01 | en_US |
dc.description | Conference Paper | en_US |
dc.description.abstract | We outline a distributed coding technique for images captured from sensors with overlapping fields of view in a sensor network. First, images from correlated views are roughly registered (relative to a sensor of primary interest) via a low-bandwidth data-sharing method involving image feature points and feature point correspondence. An area of overlap is then identified, and each sensor transmits a low-resolution version of the common image block to the receiver, amortizing the coding cost for that block among the set of sensors. Super-resolution techniques are finally employed at the receiver to reconstruct a high-resolution version of the common block. We discuss the registration and super-resolution techniques used and present examples of each step in the proposed coding process. A numerical analysis illustrating the potential coding benefit follows, and we conclude with a brief discussion of the key issues remaining to be resolved on the path to coder robustness. | en_US |
dc.identifier.citation | R. Wagner, R. D. Nowak and R. G. Baraniuk, "Distributed Image Compression for Sensor Networks using Correspondence Analysis and Super-Resolution," 2003. | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/ICIP.2003.1247032 | en_US |
dc.identifier.uri | https://hdl.handle.net/1911/20244 | en_US |
dc.language.iso | eng | en_US |
dc.subject | sensor networks | en_US |
dc.subject | distributed image compression | en_US |
dc.subject | super-resolution | en_US |
dc.subject | correspondence analysis | en_US |
dc.subject.keyword | sensor networks | en_US |
dc.subject.keyword | distributed image compression | en_US |
dc.subject.keyword | super-resolution | en_US |
dc.subject.keyword | correspondence analysis | en_US |
dc.subject.other | Image Processing and Pattern analysis | en_US |
dc.title | Distributed Image Compression for Sensor Networks using Correspondence Analysis and Super-Resolution | en_US |
dc.type | Conference paper | en_US |
dc.type.dcmi | Text | en_US |