This thesis introduces imaging algorithms for three-dimensional data analysis and classification using confocal microscopy. The third dimension, depth information, is provided through the optical sectioning property of the confocal microscope. The theme of this thesis is to develop imaging techniques that extend beyond the traditional two-dimensional (2-D) spatial coordinate system into an augmented three-dimensional (3-D) world where analysis, interpretation, and the eventual classification of data is greatly enhanced. In the development of the proposed 3-D algorithms, three main objectives were sought: (1) establish proper 3-D mathematical extensions and practical implementations of 2-D standard formulations; (2) ensure that the process of classification overcomes the burden imposed by dependence in size and orientation through applications of the principal component transform and the log-spherical plot; and (3) address such issues as memory management and accelerated processing to reach the final objective of data recognition and classification effectively.
