Image processing by two-dimensional recursive filters using the Fornasini-Marchesini model
ABSTRACT 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.
Conference Paper: A 2-D IIR neural hybrid filter for image processing[Show abstract] [Hide abstract]
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.Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on; 05/1994