000063805 001__ 63805
000063805 005__ 20190416220414.0
000063805 0247_ $$2doi$$a10.1109/TSP.2007.894257
000063805 022__ $$a1053-587X
000063805 02470 $$2DAR$$a10940
000063805 02470 $$2ISI$$a000247488900012
000063805 037__ $$aARTICLE
000063805 245__ $$aSuper-Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods
000063805 269__ $$a2007
000063805 260__ $$bInstitute of Electrical and Electronics Engineers$$c2007
000063805 336__ $$aJournal Articles
000063805 520__ $$aIn many applications, the sampling frequency is limited by the physical characteristics of the components: the pixel pitch, the rate of the A/D converter, etc. A low-pass filter is then often applied before the sampling operation to avoid aliasing. However, when multiple copies are available, it is possible to use the information that is inherently present in the aliasing to reconstruct a higher resolution signal. If the different copies have unknown relative offsets, this is a non-linear problem in the offsets and the signal coefficients. They are not easily separable in the set of equations describing the super-resolution problem. Thus, we perform joint registration and reconstruction from multiple unregistered sets of samples. We give a mathematical formulation for the problem when there are M sets of N samples of a signal that is described by L expansion coefficients. We prove that the solution of the registration and reconstruction problem is generically unique if MN>= L+M-1. We describe two subspace-based methods to compute this solution. Their complexity is analyzed, and some heuristic methods are proposed. Finally, some numerical simulation results on one and two-dimensional signals are given to show the performance of these methods.
000063805 6531_ $$aaliasing
000063805 6531_ $$asampling
000063805 6531_ $$aoffset estimation
000063805 6531_ $$ashift estimation
000063805 6531_ $$aimage registration
000063805 6531_ $$asuper-resolution
000063805 6531_ $$aIVRG
000063805 6531_ $$aNCCR-MICS/CL1
000063805 6531_ $$aNCCR-MICS
000063805 700__ $$0241125$$g126649$$aVandewalle, Patrick
000063805 700__ $$0244018$$g115222$$aSbaiz, Luciano
000063805 700__ $$aVandewalle, Joos
000063805 700__ $$aVetterli, Martin$$g107537$$0240184
000063805 773__ $$j55$$tIEEE Transactions on Signal Processing$$k7, Part 2$$q3687-3703
000063805 8564_ $$uhttp://lcav.epfl.ch/reproducible_research/VandewalleSVV06/$$zURL
000063805 8564_ $$uhttps://infoscience.epfl.ch/record/63805/files/VandewalleSVV07.pdf$$zn/a$$s1023270$$yn/a
000063805 8564_ $$uhttps://infoscience.epfl.ch/record/63805/files/VandewalleSVV07_code_rr.zip$$s2930354
000063805 909C0 $$xU10434$$0252056$$pLCAV
000063805 909C0 $$pIVRL$$xU10429$$0252320
000063805 909CO $$qGLOBAL_SET$$pIC$$particle$$ooai:infoscience.tind.io:63805
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000063805 937__ $$aLCAV-ARTICLE-2006-001
000063805 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000063805 980__ $$aARTICLE