Abstract
In the preceding chapters, the design and analysis of recursive and nonrecur-sive one-dimensional (1-D) and two-dimensional (2-D) digital filters have been discussed for the case of deterministic input signals. However, in situations such as satellite and radar imaging, knowledge of the original image is not deterministically available. Each pixel is considered as a random variable and the image is thought of as a sample of an ensemble of images. For simplicity in modeling, the image is assumed to have a Gaussian distribution which can be specified uniquely by its first- and second-order moments (mean and covariances). To perform the estimation and filtering process, the image should be represented by an appropriate statistical model.
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© 1989 Springer Science+Business Media New York
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King, R., Ahmadi, M., Gorgui-Naguib, R., Kwabwe, A., Azimi-Sadjadi, M. (1989). Image Modeling. In: Digital Filtering in One and Two Dimensions. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-0918-3_10
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DOI: https://doi.org/10.1007/978-1-4899-0918-3_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4899-0920-6
Online ISBN: 978-1-4899-0918-3
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