Gray-scale granulometries Develop a satisfactory asymptotic theory and investigate optimization and robustness. Multivariate bandpass filters Pursue optimization through multivariate generalized functions. Logical granulometries Find satisfactory image models for analytic characterizations of optimality and adaptivity. Develop random image models whose typical realizations satisfy useful geometric constraints. Application to texture classification and filtering Develop a good theoretical understanding of morphologically constrained GRFs for use in texture classification algorithms that can be used for detection of breast cancer.
Parameter estimation Investigate the probability distribution of the pattern spectrum.
Boolean Random Models 1. General germ-grain models Consider how erroneous estimates of gamma distribution parameters impact asymptotic distributional representations. Estimation Find estimates for needed parameters. Study simple parametric Boolean random function models for gray-scale images, and then focus on the problem of estimating model parameters.