In this paper, we present optimal parallel algorithms for optical clustering on a mesh-connected computer.Optical clustering is a clustering technique based on the principal of optical resolution, and is of particular interest in picture analysis. The algorithms we present are based on the application of parallel algorithms in computational geometry and graph theory. In particular, we show that given a setS ofN points in the Euclidean plane, the following problems can be solved in optimal\(O\left( {\sqrt N } \right)\) time on a mesh-connected computer of sizeN. 1. Determine the optical clusters ofS with respect to a given separation parameter. 2. Given an interval [a, b] representing the number of optical clusters desired in the clustering ofS, determine the range of the separation parameter that will result in such an optical clustering.