LEADER 02571nam 2200553Ia 450 001 9910739437803321 005 20200520144314.0 010 $a1-299-33549-7 010 $a1-4614-6381-5 024 7 $a10.1007/978-1-4614-6381-8 035 $a(OCoLC)841800220 035 $a(MiFhGG)GVRL6WGP 035 $a(CKB)2670000000336415 035 $a(MiAaPQ)EBC1106290 035 $a(EXLCZ)992670000000336415 100 $a20130219d2013 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aSparse representations and compressive sensing for imaging and vision /$fVishal M. Patel, Rama Chellappa 205 $a1st ed. 2013. 210 $aNew York $cSpringer$d2013 215 $a1 online resource (x, 102 pages) $cillustrations (some color) 225 0$aSpringerBriefs in electrical and computer engineering 300 $aDescription based upon print version of record. 311 $a1-4614-6380-7 320 $aIncludes bibliographical references. 327 $aIntroduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks. 330 $aCompressed sensing or compressive sensing is a new concept in signal processing where one measures a small number of non-adaptive linear combinations of the signal.  These measurements are usually much smaller than the number of samples that define the signal.  From these small numbers of measurements, the signal is then reconstructed by non-linear procedure.  Compressed sensing has recently emerged as a powerful tool for efficiently processing data in non-traditional ways.  In this book, we highlight some of the key mathematical insights underlying sparse representation and compressed sensing and illustrate the role of these theories in classical vision, imaging and biometrics problems. 410 0$aSpringerBriefs in electrical and computer engineering. 606 $aImaging 606 $aSignal processing$xMathematics 606 $aVision 615 0$aImaging. 615 0$aSignal processing$xMathematics. 615 0$aVision. 676 $a621.382 676 $a621.3822 700 $aPatel$b Vishal M$01415537 701 $aChellappa$b Rama$0491442 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910739437803321 996 $aSparse representations and compressive sensing for imaging and vision$94186922 997 $aUNINA