Tiled-Block Image Reconstruction by Wavelet- Based, Parallel-Filtered Back-Projection
We demonstrate an algorithm, relevant to tomography sensor systems, to obtain images from the parallel reconstruction of essentially localized elements at different scales. This is achieved by combining methodology to reconstruct images from limited and/or truncated data, with the time-frequency cap...
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| Veröffentlicht in: | IEEE sensors journal 2016-06, Vol.16 (12), p.4839-4846 |
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| creator | Guevara Escobedo, Jorge Ozanyan, Krikor B. |
| description | We demonstrate an algorithm, relevant to tomography sensor systems, to obtain images from the parallel reconstruction of essentially localized elements at different scales. This is achieved by combining methodology to reconstruct images from limited and/or truncated data, with the time-frequency capabilities of the wavelet transform. Multiscale, as well as time-frequency, localization properties of the separable two-dimensional wavelet transform are exploited as an approach for faster reconstruction. The speedup is realized not only by reducing the computation load on a single processor, but also by achieving the parallel reconstruction of several tiled blocks. With tiled-block image reconstruction by wavelet-based, parallel filtered back-projection (FBP), we measure more than 36 times gain in speed, compared with standard FBP. |
| doi_str_mv | 10.1109/JSEN.2016.2546182 |
| format | Article |
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With tiled-block image reconstruction by wavelet-based, parallel filtered back-projection (FBP), we measure more than 36 times gain in speed, compared with standard FBP.</description><subject>computed tomography</subject><subject>data processing algorithms</subject><subject>Filtering</subject><subject>Gain</subject><subject>Image reconstruction</subject><subject>Microprocessors</subject><subject>parallel processing</subject><subject>Reconstruction</subject><subject>Sensors</subject><subject>Time-frequency analysis</subject><subject>Tomography</subject><subject>wavelet transform</subject><subject>Wavelet transforms</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkE1PwzAMhisEEuPjByAulbhwICNumyY5smnjQxMgYIJblKYO6patI2mR9u_p2MSBky35eW3riaIzoH0AKq8fXkeP_YRC3k9YloNI9qIeMCYI8Ezsb_qUkizlH4fRUQgzSkFyxnvR9K1yWJKBq808vl_oT4xf0NTL0PjWNFW9jIt1_K6_0WFD4oEOWF7Fz9pr59CRceUa9Fh2AzMnz76e4W_oJDqw2gU83dXjaDoevQ3vyOTp9n54MyEmzWVDhNCyKJBJao3hImFJyiyWWgpMDEdjMm2lKYBaKAueWCxKm6cMOE1ZWSQ2PY4ut3tXvv5qMTRqUQWDzukl1m1QICCnuegcdOjFP3RWt37ZfaeAS8qBCSo7CraU8XUIHq1a-Wqh_VoBVRvRaiNabUSrneguc77NVIj4x3cnJc-y9AeOHXnD</recordid><startdate>20160615</startdate><enddate>20160615</enddate><creator>Guevara Escobedo, Jorge</creator><creator>Ozanyan, Krikor B.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | computed tomography data processing algorithms Filtering Gain Image reconstruction Microprocessors parallel processing Reconstruction Sensors Time-frequency analysis Tomography wavelet transform Wavelet transforms |
| title | Tiled-Block Image Reconstruction by Wavelet- Based, Parallel-Filtered Back-Projection |
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