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.
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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