02571nam 2200553Ia 450 991073943780332120200520144314.01-299-33549-71-4614-6381-510.1007/978-1-4614-6381-8(OCoLC)841800220(MiFhGG)GVRL6WGP(CKB)2670000000336415(MiAaPQ)EBC1106290(EXLCZ)99267000000033641520130219d2013 uy 0engurun|---uuuuatxtccrSparse representations and compressive sensing for imaging and vision /Vishal M. Patel, Rama Chellappa1st ed. 2013.New York Springer20131 online resource (x, 102 pages) illustrations (some color)SpringerBriefs in electrical and computer engineeringDescription based upon print version of record.1-4614-6380-7 Includes bibliographical references.Introduction -- Compressive Sensing -- Compressive Acquisition -- Compressive Sensing for Vision -- Sparse Representation-based Object Recognition -- Dictionary Learning -- Concluding Remarks.Compressed 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.SpringerBriefs in electrical and computer engineering.ImagingSignal processingMathematicsVisionImaging.Signal processingMathematics.Vision.621.382621.3822Patel Vishal M1415537Chellappa Rama491442MiAaPQMiAaPQMiAaPQBOOK9910739437803321Sparse representations and compressive sensing for imaging and vision4186922UNINA