Classification and prediction of wavelet coefficients for lossless compression of landsat images
Inspired by previous work on the modelling of wavelet coefficients, and on the observed differences between distributions of wavelet coefficients belonging to different landscapes, we present a lossless compressor of multispectral images based on the prediction of wavelet coefficients, conditioned t...
Guardado en:
| Autores principales: | , |
|---|---|
| Publicado: |
2006
|
| Materias: | |
| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v6300_n_p_Acevedo http://hdl.handle.net/20.500.12110/paper_0277786X_v6300_n_p_Acevedo |
| Aporte de: |
| id |
paper:paper_0277786X_v6300_n_p_Acevedo |
|---|---|
| record_format |
dspace |
| spelling |
paper:paper_0277786X_v6300_n_p_Acevedo2023-06-08T15:26:27Z Classification and prediction of wavelet coefficients for lossless compression of landsat images Acevedo, Daniel G. Ruedin, Ana María Clara Classification Lossless Multispectral Prediction Wavelet coefficients Classification (of information) Codes (symbols) Entropy Wavelet transforms Coded band Landsat images Multispectral images Wavelet coefficients Image compression Inspired by previous work on the modelling of wavelet coefficients, and on the observed differences between distributions of wavelet coefficients belonging to different landscapes, we present a lossless compressor of multispectral images based on the prediction of wavelet coefficients, conditioned to the landscape. This compressor operates blockwise. The wavelet transform is applied to each block, and detail coefficients from the two finest scales are predicted by means of a linear combination of other coefficients, which may belong to the same band as the predicted coefficient, or to a previously coded band. The weights for the lineal combination are estimated on-line: for each detail subband, the compressor is trained on all the detail coefficients belonging to the same class. In addition, a different band ordering is considered for each block. Differences in prediction are coded with a conditional entropy coder. Preliminary results reveal that we obtain more accurate predictions. Fil:Acevedo, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Ruedin, A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2006 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v6300_n_p_Acevedo http://hdl.handle.net/20.500.12110/paper_0277786X_v6300_n_p_Acevedo |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Classification Lossless Multispectral Prediction Wavelet coefficients Classification (of information) Codes (symbols) Entropy Wavelet transforms Coded band Landsat images Multispectral images Wavelet coefficients Image compression |
| spellingShingle |
Classification Lossless Multispectral Prediction Wavelet coefficients Classification (of information) Codes (symbols) Entropy Wavelet transforms Coded band Landsat images Multispectral images Wavelet coefficients Image compression Acevedo, Daniel G. Ruedin, Ana María Clara Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| topic_facet |
Classification Lossless Multispectral Prediction Wavelet coefficients Classification (of information) Codes (symbols) Entropy Wavelet transforms Coded band Landsat images Multispectral images Wavelet coefficients Image compression |
| description |
Inspired by previous work on the modelling of wavelet coefficients, and on the observed differences between distributions of wavelet coefficients belonging to different landscapes, we present a lossless compressor of multispectral images based on the prediction of wavelet coefficients, conditioned to the landscape. This compressor operates blockwise. The wavelet transform is applied to each block, and detail coefficients from the two finest scales are predicted by means of a linear combination of other coefficients, which may belong to the same band as the predicted coefficient, or to a previously coded band. The weights for the lineal combination are estimated on-line: for each detail subband, the compressor is trained on all the detail coefficients belonging to the same class. In addition, a different band ordering is considered for each block. Differences in prediction are coded with a conditional entropy coder. Preliminary results reveal that we obtain more accurate predictions. |
| author |
Acevedo, Daniel G. Ruedin, Ana María Clara |
| author_facet |
Acevedo, Daniel G. Ruedin, Ana María Clara |
| author_sort |
Acevedo, Daniel G. |
| title |
Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| title_short |
Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| title_full |
Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| title_fullStr |
Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| title_full_unstemmed |
Classification and prediction of wavelet coefficients for lossless compression of landsat images |
| title_sort |
classification and prediction of wavelet coefficients for lossless compression of landsat images |
| publishDate |
2006 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_0277786X_v6300_n_p_Acevedo http://hdl.handle.net/20.500.12110/paper_0277786X_v6300_n_p_Acevedo |
| work_keys_str_mv |
AT acevedodanielg classificationandpredictionofwaveletcoefficientsforlosslesscompressionoflandsatimages AT ruedinanamariaclara classificationandpredictionofwaveletcoefficientsforlosslesscompressionoflandsatimages |
| _version_ |
1768543607667556352 |