New spectral image compression method based on an optimal phase coding and the RMS duration principle
By using only phase information, this paper describes a new spectral lossy compression method which can: reduce required memories; adaptively retrieve original images by using only spectral phase information; increase the peak-to-correlation energy (PCE) at the output of the correlator; and be easil...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Institute of Physics
2010
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| Online Access: | http://hdl.handle.net/20.500.11937/31908 |
| _version_ | 1848753514964058112 |
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| author | Alfalou, A. Elbouz, M. Mansour, Ali Keryer, G. |
| author_facet | Alfalou, A. Elbouz, M. Mansour, Ali Keryer, G. |
| author_sort | Alfalou, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | By using only phase information, this paper describes a new spectral lossy compression method which can: reduce required memories; adaptively retrieve original images by using only spectral phase information; increase the peak-to-correlation energy (PCE) at the output of the correlator; and be easily employed in major encryption techniques. To increase the compression ratio of the proposed method, an optimal phase coding based on 'a fading grid' is performed. In fact, a variable number of quantization bits has been used to quantize phase information depending on the importance of the spectral phases. The phase information could be classified according to the concept of 'RMS duration'. Many simulations have been carried out. Our experimental results corroborate the performance of the proposed new method. |
| first_indexed | 2025-11-14T08:25:44Z |
| format | Journal Article |
| id | curtin-20.500.11937-31908 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:25:44Z |
| publishDate | 2010 |
| publisher | Institute of Physics |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-319082018-03-29T09:09:14Z New spectral image compression method based on an optimal phase coding and the RMS duration principle Alfalou, A. Elbouz, M. Mansour, Ali Keryer, G. By using only phase information, this paper describes a new spectral lossy compression method which can: reduce required memories; adaptively retrieve original images by using only spectral phase information; increase the peak-to-correlation energy (PCE) at the output of the correlator; and be easily employed in major encryption techniques. To increase the compression ratio of the proposed method, an optimal phase coding based on 'a fading grid' is performed. In fact, a variable number of quantization bits has been used to quantize phase information depending on the importance of the spectral phases. The phase information could be classified according to the concept of 'RMS duration'. Many simulations have been carried out. Our experimental results corroborate the performance of the proposed new method. 2010 Journal Article http://hdl.handle.net/20.500.11937/31908 10.1088/2040-8978/12/11/115403 Institute of Physics restricted |
| spellingShingle | Alfalou, A. Elbouz, M. Mansour, Ali Keryer, G. New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title | New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title_full | New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title_fullStr | New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title_full_unstemmed | New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title_short | New spectral image compression method based on an optimal phase coding and the RMS duration principle |
| title_sort | new spectral image compression method based on an optimal phase coding and the rms duration principle |
| url | http://hdl.handle.net/20.500.11937/31908 |