A new approach to non-homogeneous image modelling for recursive filtering problems is developed. The main assumption is that the whole non-homogeneous image can be modelled by a collection of homogeneous open subregions where the 2-D signal is regular enough to be well described by a smooth two-dimensional gaussian process. The boundary points between two adjacent homogeneous subregions are the image edges which represent sharp discontinuities (inhomogeneities) in the signal distribution. A non-stationary state-space representation with structural information on the image non-homogeneity is obtained. This allows the model to vary in an adaptive manner according to the presence of spatial discontinuities. Finally, the reported simulation results show high filter performances.

A non-stationary adaptive model for recursive image filtering

GERMANI, Alfredo;
1991-01-01

Abstract

A new approach to non-homogeneous image modelling for recursive filtering problems is developed. The main assumption is that the whole non-homogeneous image can be modelled by a collection of homogeneous open subregions where the 2-D signal is regular enough to be well described by a smooth two-dimensional gaussian process. The boundary points between two adjacent homogeneous subregions are the image edges which represent sharp discontinuities (inhomogeneities) in the signal distribution. A non-stationary state-space representation with structural information on the image non-homogeneity is obtained. This allows the model to vary in an adaptive manner according to the presence of spatial discontinuities. Finally, the reported simulation results show high filter performances.
1991
9780080401744
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/31143
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