Linear Models in Spatial Discriminant Analysis
This paper reports on developments of a linear model, proposed in Haslett and Horgan (1985), for the reconstruction of binary (2 colour) images corrupted by additive Gaussian noise. The proposed method involved constructing a simple linear filter of the image, and thresholding the result. This very simple method was competitive with others, much more complicated, in terms of accuracy and speed. Further, by virtue of its close affinities with classical statistical methods of multivariate linear discriminant analysis, it yielded important and easily interpretable qualifications to any given reconstruction, notably (a) an estimated value for the proportion of pixels correctly classified and (b) posterior probabilities for the colour of each pixel.
KeywordsCovariance Remotely Sense
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