We present a maximum likelihood (Ml) solution to the problem of obtaining high-resolution images from sequences of noisy, blurred, and low-resolution images. In our formulation, t...
Nathan A. Woods, Nikolas P. Galatsanos, Aggelos K....
Two moving-window methods, using either flat or Gaussian weighted windows, for local thresholding with Robust Automatic Threshold Selection are developed. The results show that fa...
Michael H. F. Wilkinson, T. Wijbenga, G. de Vries,...
A new probabilistic image segmentation model based on hypothesis testing and Gibbs Random Fields is introduced. First, a probabilistic difference measure derived from a set of hyp...