Dane Barney

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We investigate the ability to derive meaningful information from decompressed imaging spectrometer data. Hyperspectral images are compressed with near-lossless and lossy coding methods. Linear prediction between the bands is used in both cases. Each band is predicted by a previously transmitted band. The residual is formed by subtracting the prediction from(More)
For Deaf people, access to the mobile telephone network in the United States is currently limited to text messaging, forcing communication in English as opposed to American Sign Language (ASL), the preferred language. Because ASL is a visual language, mobile video phones have the potential to give Deaf people access to real-time mobile communication in(More)
Algorithms for near-lossless compression of hyperspectral images are presented. They guarantee that the intensity of any pixel in the decompressed image(s) differs from its original value by no more than a user-specified quantity To reduce the bit rate required to code images while providing significantly more compression than lossless algorithms, linear(More)
For Deaf people, access to the mobile telephone network in the United States is currently limited to text messaging, forcing communication in English as opposed to American Sign Language (ASL), the preferred language. Because ASL is a visual language, mobile video phones have the potential to give Deaf people access to real-time mobile communication in(More)
Algorithms for lossless and lossy compression of hyperspectral images are presented. To greatly reduce the bit rate required to code images and to exploit the large amount of inter-band correlation, linear prediction between the bands is used. Each band, except the first one, is predicted by previously transmitted band. Once the prediction is formed, it is(More)
JPEG-2000, the successor to JPEG, is emerging as an attractive candidate for the future de facto image compression standard. However, while it offers superior results over most other image compression techniques, it comes with a long list of features and options, and consequently a highly complex algorithm. We have developed an image coder that can compete(More)
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