Recursive estimation of two-dimensional processes with application to image processing

DOI10.1007/BF01600057zbMath0629.93062MaRDI QIDQ1094380

Bijan Lashgari, Leonard M. Silverman

Publication date: 1986

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

zbMATH Keywords

image restoration2-dimensional estimation2-dimensional recursive minimum variance error (MVE) estimationRoesser-CRSD stochastic model

Mathematics Subject Classification ID

Gaussian processes (60G15) Estimation and detection in stochastic control theory (93E10) Applications of statistics (62P99) Artificial intelligence (68T99) Sequential estimation (62L12)

Related Items (4)

Optimal design of 2D FIR filters with quadrantally symmetric properties using fractional derivative constraints ⋮ Image modeling based on a 2-D stochastic subspace system identification algorithm ⋮ A stochastic subspace system identification algorithm for state-space systems in the general 2-D Roesser model form ⋮ Subspace algorithms for identifying separable-in-denominator 2D systems with deterministic–stochastic inputs

Cites Work

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• Singular value decomposition and least squares solutions
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• Nonlinear Restoration of Noisy Images
• A discrete state-space model for linear image processing
• State-space realization theory of two-dimensional filters
• Hierarchic recursive image enhancement
• Kalman filtering in two dimensions
• Realization and stabilization of 2-d systems
• Approximation of 2-D separable in denominator filters
• Modeling of two-dimensional covariance functions with application to image restoration

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