Image processing by two-dimensional recursive filters using the Fornasini-Marchesini model

Faculty of Engineering, Tottori University, Tottori, Japan 680
Electronics and Communications in Japan (Part III Fundamental Electronic Science) (Impact Factor: 0.14). 01/1992; 75(5):60 - 68. DOI: 10.1002/ecjc.4430750506


This paper considers a simple two-dimensional (2-D) IIR filter based on the Fornasini-Marchesini local state-space (LSS) model. It is shown that if image processing is carried out using such filters from four directions, smoothing, edge detection or edge enhancement can be achieved without any distortion. The proposed technique allows one to flexibly perform the forementioned filtering by choosing three parameters. Moreover, filter analysis including stability is easy due to using a well-known 2-D LSS model. Finally, some examples are given to illustrate the utility of the proposed technique.

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    ABSTRACT: A two-dimensional (2-D) IIR neural hybrid (2DINH) filter is proposed for image processing. This 2DINH filter consists of the cascade connection of a 2-D IIR linear filter followed by a neural filter. The proposed filter can be applied to smoothing for the images corrupted with Gaussian noise and/or impulsive noise and to edge detection for the images corrupted with Gaussian noise. The parameters of a neural filter are adjustable by a learning algorithm to adapt itself to the property of an image to be processed. Finally, some examples are given to illustrate the utility of the proposed filter.
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