Association of adaptative smoothing and Markovian models for detection of valley bottoms on strongly noisy images (nondestructive testing)
Robert Azencott, B. Chalmond, François Coldefy · 2003
The paper is related to a nondestructive control industrial task: the detection of defects in gamma radiographic images. The images are very noisy and have a strong luminosity gradient. The authors adopt a Bayes-Markov model in order to estimate the noise, the gradient and the defects. The proposed model is general and can be used in other situations for detecting valley bottoms in noisy images.>