{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T04:31:59Z","timestamp":1746073919870,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>In this work we propose several parallel algorithms to compute the two-dimensional discrete wavelet transform (2D-DWT), exploiting the available hardware resources. In particular, we will explore OpenMP optimized versions of 2D-DWT over a multicore platform and we will also develop CUDA-based 2D-DWT algorithms which are able to run on GPUs (Graphics Processing Unit). The proposed algorithms are based on several 2D-DWT computation approaches as (1) filter-bank convolution, (2) lifting transform and (3) matrix convolution, so we can determine which of them better adapts to our parallel versions. All proposed algorithms are based on the Daubechies 9\/7 filter which is widely used in image\/video compression.<\/jats:p>","DOI":"10.3233\/978-1-61499-041-3-151","type":"book-chapter","created":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:30:51Z","timestamp":1739979051000},"source":"Crossref","is-referenced-by-count":1,"title":["Speeding-up the discrete wavelet transform computation with multicore and GPU-based algorithms"],"prefix":"10.3233","author":[{"family":"Galiano V.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"L&oacute;pez O.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Malumbres M.P.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Migall&oacute;n H.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Advances in Parallel Computing","Applications, Tools and Techniques on the Road to Exascale Computing"],"original-title":[],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T15:51:09Z","timestamp":1739980269000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0927-5452&volume=22&spage=151"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-041-3-151","relation":{},"ISSN":["0927-5452"],"issn-type":[{"value":"0927-5452","type":"print"}],"subject":[],"published":{"date-parts":[[2012]]}}}