Spectrum decomposition for image/signal coding
In conventional subband/wavelet image coding, the subband decomposition is performed on the spatial-domain image. Here, we introduce a novel decomposition where the subband decomposition is performed on the global DCT spectrum of the image. That is, the two-dimensional spectrum rather than the image...
| Main Authors: | , |
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| Format: | Journal Article |
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I E E E
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/33536 |
| _version_ | 1848753973869150208 |
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| author | Lin, Jianyu Smith, M. |
| author_facet | Lin, Jianyu Smith, M. |
| author_sort | Lin, Jianyu |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In conventional subband/wavelet image coding, the subband decomposition is performed on the spatial-domain image. Here, we introduce a novel decomposition where the subband decomposition is performed on the global DCT spectrum of the image. That is, the two-dimensional spectrum rather than the image is represented by a sum of basis functions, each weighted by the transform coefficients. The distinct features of this decomposition are analyzed from a transform perspective. This spectral subband decomposition is then used as the basis for a new image coder, building on the condensed wavelet packet (CWP) algorithm. Ironically, this new method is shown to have lower arithmetic complexity than conventional subband/wavelet coders that directly decompose a time or spatial domain signal. Comparisons of the new method against conventional subband/wavelet coders that use the popular 9/7 dyadic decomposition, condensed wavelet packets, and generalized lapped orthogonal transforms, show that the new method has lower complexity and higher compression performance. |
| first_indexed | 2025-11-14T08:33:02Z |
| format | Journal Article |
| id | curtin-20.500.11937-33536 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:33:02Z |
| publishDate | 2013 |
| publisher | I E E E |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-335362017-09-13T15:31:15Z Spectrum decomposition for image/signal coding Lin, Jianyu Smith, M. decomposition of spectrum condensed wavelet packets overlapped block transform sparse transform for coding and compressive sampling/compressed sensing In conventional subband/wavelet image coding, the subband decomposition is performed on the spatial-domain image. Here, we introduce a novel decomposition where the subband decomposition is performed on the global DCT spectrum of the image. That is, the two-dimensional spectrum rather than the image is represented by a sum of basis functions, each weighted by the transform coefficients. The distinct features of this decomposition are analyzed from a transform perspective. This spectral subband decomposition is then used as the basis for a new image coder, building on the condensed wavelet packet (CWP) algorithm. Ironically, this new method is shown to have lower arithmetic complexity than conventional subband/wavelet coders that directly decompose a time or spatial domain signal. Comparisons of the new method against conventional subband/wavelet coders that use the popular 9/7 dyadic decomposition, condensed wavelet packets, and generalized lapped orthogonal transforms, show that the new method has lower complexity and higher compression performance. 2013 Journal Article http://hdl.handle.net/20.500.11937/33536 10.1109/TSP.2012.2231680 I E E E restricted |
| spellingShingle | decomposition of spectrum condensed wavelet packets overlapped block transform sparse transform for coding and compressive sampling/compressed sensing Lin, Jianyu Smith, M. Spectrum decomposition for image/signal coding |
| title | Spectrum decomposition for image/signal coding |
| title_full | Spectrum decomposition for image/signal coding |
| title_fullStr | Spectrum decomposition for image/signal coding |
| title_full_unstemmed | Spectrum decomposition for image/signal coding |
| title_short | Spectrum decomposition for image/signal coding |
| title_sort | spectrum decomposition for image/signal coding |
| topic | decomposition of spectrum condensed wavelet packets overlapped block transform sparse transform for coding and compressive sampling/compressed sensing |
| url | http://hdl.handle.net/20.500.11937/33536 |