Advisor: Rosalind W. Picard.
Other Committee Members:
A new approach to high-order-conditional probability density estimation is developed, based on a partitioning of conditioning space via decision trees. The technique is applied to image compression, image restoration, and texture synthesis, and the results compared with those obtained by standard mixture density and linear regression models. By applying the technique to subband-domain processing, some evidence is provided to support the following statement: the appropriate tradeoff between spatial and spectral localization in linear preprocessing shifts towards greater spatial localization when subbands are processed in a way that exploits interdependence.
Last modified: Wed Jan 19 14:46:32 EST 2000