SVD lossy adaptive encoding of 3D digital images for ROI progressive transmission
In this paper, we propose an algorithm for lossy adaptive encoding of digital three-dimensional (3D) images based on singular value decomposition (SVD). This encoding allows us to design algorithms for progressive transmission and reconstruction of the 3D image, for one or several selected regions o...
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| Veröffentlicht in: | Image and vision computing 2010-03, Vol.28 (3), p.449-457 |
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| container_title | Image and vision computing |
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| creator | Baeza, Ismael Verdoy, José-Antonio Villanueva, Rafael-Jacinto Villanueva-Oller, Javier |
| description | In this paper, we propose an algorithm for lossy adaptive encoding of digital three-dimensional (3D) images based on singular value decomposition (SVD). This encoding allows us to design algorithms for progressive transmission and reconstruction of the 3D image, for one or several selected regions of interest (ROI) avoiding redundancy in data transmission. The main characteristic of the proposed algorithms is that the ROIs can be selected during the transmission process and it is not necessary to re-encode the image again to transmit the data corresponding to the selected ROI. An example with a data set of a CT scan consisting of 93 parallel slices where we added an implanted tumor (the ROI in this example) and a comparative with JPEG2000 are given. |
| doi_str_mv | 10.1016/j.imavis.2009.07.004 |
| format | Article |
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| issn | 0262-8856 1872-8138 |
| language | eng |
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| source | Elsevier ScienceDirect Journals Complete |
| subjects | 3D digital images Lossy progressive transmission Region of interest (ROI) transmission Singular value decomposition encoding |
| title | SVD lossy adaptive encoding of 3D digital images for ROI progressive transmission |
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