Title :
A Statistical model for the warp matrix in super-resolution video reconstruction
Author :
Costa, Guilherme H. ; Bermudez, José C M
Author_Institution :
Fed. Univ. of Santa Catarina, Florianopolis
Abstract :
This paper advances in the analysis of the least mean square (LMS) algorithm applied to super-resolution reconstruction (SRR) of an image sequence. SRR of image sequences is highly dependent on the quality of the registration stage. When motion between frames is unknown and has to be estimated, the best available statistical model still requires the numerical estimation of the moments of the registration (warp) matrix. In this work we derive an analytical model for these moments for Gaussian registration errors. The new model allows for different boundary conditions. Monte Carlo simulation results illustrate the accuracy of the new analytical model.
Keywords :
Gaussian processes; Monte Carlo methods; image reconstruction; image registration; image sequences; matrix algebra; video signal processing; Gaussian registration errors; Monte Carlo simulation; image sequence; least mean square algorithm; statistical model; super-resolution video reconstruction; warp matrix; Algorithm design and analysis; Analytical models; Boundary conditions; Image analysis; Image reconstruction; Image resolution; Image sequence analysis; Image sequences; Least squares approximation; Motion estimation; LMS; Super-resolution reconstruction; adaptive filtering; registration error; statistical analysis;
Conference_Titel :
Telecommunications Symposium, 2006 International
Conference_Location :
Fortaleza, Ceara
Print_ISBN :
978-85-89748-04-9
Electronic_ISBN :
978-85-89748-04-9
DOI :
10.1109/ITS.2006.4433384
