TY - GEN
T1 - Blind filter identification and image superresolution using subspace methods
AU - Gastaud, Muriel
AU - Ladjal, Saïd
AU - Maître, Henri
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Subspace methods are a powerful tool to recover unknown filters by looking at the second order statistics of various signals originating from the same source (also called a SIMO problem). An extension to the multiple source case is also possible and has been investigated in the literature. In this paper we show how the blind superresolution problem can be solved by this tool. We first present the problem of superresolution as a multiple input multiple output (MIMO) one. We show that the subspace method can not be used, as is, to recover the filters affecting each image, and we present two possible solutions, based on the statistical characteristics of the images to solve this problem. Experiments are shown which validate these ideas.
AB - Subspace methods are a powerful tool to recover unknown filters by looking at the second order statistics of various signals originating from the same source (also called a SIMO problem). An extension to the multiple source case is also possible and has been investigated in the literature. In this paper we show how the blind superresolution problem can be solved by this tool. We first present the problem of superresolution as a multiple input multiple output (MIMO) one. We show that the subspace method can not be used, as is, to recover the filters affecting each image, and we present two possible solutions, based on the statistical characteristics of the images to solve this problem. Experiments are shown which validate these ideas.
M3 - Conference contribution
AN - SCOPUS:57349176394
SN - 9788392134022
T3 - European Signal Processing Conference
SP - 1078
EP - 1082
BT - 15th European Signal Processing Conference, EUSIPCO 2007 - Proceedings
T2 - 15th European Signal Processing Conference, EUSIPCO 2007
Y2 - 3 September 2007 through 7 September 2007
ER -