http://www.cnr.it/ontology/cnr/individuo/prodotto/ID80780
Inter-band Distortion Allocation in Lossy Hyperspectral Data Compression (Contributo in atti di convegno)
- Type
- Label
- Inter-band Distortion Allocation in Lossy Hyperspectral Data Compression (Contributo in atti di convegno) (literal)
- Anno
- 2008-01-01T00:00:00+01:00 (literal)
- Alternative label
L. Santurri, B. Aiazzi, L. Alparone, S. Baronti, C. Lastri (2008)
Inter-band Distortion Allocation in Lossy Hyperspectral Data Compression
in On-Board Payload Data Compression Workshop, ESA/ESTEC, Noordwijk, The Neth, 26-27 Jun. 2008
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- L. Santurri, B. Aiazzi, L. Alparone, S. Baronti, C. Lastri (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- On-Board Payload Data Compression Workshop OPBDC-2008 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- In Proc. ESA OBPDC 2008, On-Board Payload Data Compression Workshop, ESA/ESTEC, Noordwijk, The Netherlands, 26-27 Jun. 2008. (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- L. Santurri, B. Aiazzi, S. Baronti, C. Lastri: IFAC-CNR.
L. Alparone: DET Università degli studi di Firenze. (literal)
- Titolo
- Inter-band Distortion Allocation in Lossy Hyperspectral Data Compression (literal)
- Abstract
- The problem of distortion allocation varying with wavelength in lossy compression of hyperspectral imagery is investigated.
Distortion is generally measured either as maximum absolute deviation (MAD) for near-lossless methods, e.g.
differential pulse code modulation (DPCM), or as mean square error (MSE) for lossy methods (e.g. spectral decorrelation
followed by JPEG 2000). Also the absolute angular error, or spectral angle mapper (SAM), is used to quantify spectral
distortion. A band add-on (BAO) technique was recently introduced to calculate a modified version of SAM. Spectral
bands are iteratively selected in order to increase the angular separation between two pixel spectra by exploiting a
mathematical decomposition of SAM. As a consequence, only a subset of the original hyperspectral bands contributes
to the new distance metrics, referred to as BAO-SAM, whose operational definition guarantees its monotonicity as the
number of bands increases. Two strategies of inter-band distortion allocation are compared: given a target average bit
rate, distortion, either MAD or MSE, may be set to be constant varying with wavelength. Otherwise it may be allocated
proportionally to the noise level on each band, according to the virtually-lossless protocol. Thus, a different quantization
step size depending on the estimated standard deviation of the noise, is used to quantize either prediction residuals
(DPCM) or wavelet coefficients (JPEG 2000) of each spectral band, thereby determining band-varying MAD/MSE
values. Comparisons with the uncompressed originals show that the average spectral angle mapper (SAM) is minimized
by constant distortion allocation. Conversely, the average BAO-SAM is minimized by the noise-adjusted variable spectral
distortion allocation according to the virtually lossless protocol. (literal)
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