1986
DOI: 10.1109/proc.1986.13504
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Statistical model-based algorithms for image analysis

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Cited by 89 publications
(34 citation statements)
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“…The tendency to produce a "noisy" result is not surprising since no attempt has been made to model spatial correlation in the labelled image. One method of encouraging the formation of regions in the segmented image to use a Bayesian approach with a Markov process describing the region prior [2], [12], [7]. In our case we simply apply a median filter to the segmented image, as shown in Fig.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The tendency to produce a "noisy" result is not surprising since no attempt has been made to model spatial correlation in the labelled image. One method of encouraging the formation of regions in the segmented image to use a Bayesian approach with a Markov process describing the region prior [2], [12], [7]. In our case we simply apply a median filter to the segmented image, as shown in Fig.…”
Section: Discussionmentioning
confidence: 99%
“…In this work we investigate the use of a two dimensional AR model. AR models have been successful in modelling image texture in several image processing applications, for example optical aerial images [12]. We apply a two dimensional AR model to complex amplitude data in order to partition the image into regions eharaeterised by distinct second order statistics.…”
Section: Introductionmentioning
confidence: 99%
“…In simple image subtraction, the measure of change is based on the difference between corresponding pixel values. Adaptive techniques (Therrien et al 1986, Lee et al 1986, Ca rlotto et al 1992 use information over larger areas (e.g., within a sliding window, regions of similar material type, or the entire image) to model and predict the two images from each other. The difference between the actual and predicted image is used as a measure of change.…”
Section: Change Detectionmentioning
confidence: 99%
“…One of these, the Reed Xiaoli (RX) algorithm [2], detects objects of known shape/shape that are spectrally different from the immediate background. Autoregressive [3] and fractal models [4] have been also proposed for detecting manmade objects in textured backgrounds. Many of these algorithms use some form of sliding window to find objects of a given size.…”
Section: Introductionmentioning
confidence: 99%