TY - GEN
T1 - Estimation of reconstruction error surfaces of non-stationary Gaussian images
AU - Rodriguez-Saldana, Daniel
AU - Kazakov, Vladimir A.
AU - Iturri-Hinojosa, Luis Alejandro
PY - 2012
Y1 - 2012
N2 - This paper explores the reconstruction of non-stationary Gaussian images. The non-stationary image character is only given in space but not in time. The reconstruction method is specified on the basis of the conditional mean rule when the quantity of samples is limited. A spatial covariance function is proposed to describe the non-stationary nature of Gaussian image. This method provides the surface of the optimal reconstruction error functions in the whole space domain of the image. Furthermore, an easy statistical description of stationary or non-stationary image is directly obtained by this methodology in any spatial region with these properties.
AB - This paper explores the reconstruction of non-stationary Gaussian images. The non-stationary image character is only given in space but not in time. The reconstruction method is specified on the basis of the conditional mean rule when the quantity of samples is limited. A spatial covariance function is proposed to describe the non-stationary nature of Gaussian image. This method provides the surface of the optimal reconstruction error functions in the whole space domain of the image. Furthermore, an easy statistical description of stationary or non-stationary image is directly obtained by this methodology in any spatial region with these properties.
KW - Gaussian random fields
KW - image reconstruction
KW - mean square reconstruction error surfaces
KW - nonstationary process
UR - http://www.scopus.com/inward/record.url?scp=84870827224&partnerID=8YFLogxK
M3 - Contribución a la conferencia
AN - SCOPUS:84870827224
SN - 9781467344975
T3 - World Automation Congress Proceedings
BT - 2012 World Automation Congress, WAC 2012
T2 - 2012 World Automation Congress, WAC 2012
Y2 - 24 June 2012 through 28 June 2012
ER -