Detection of objects is an important task of computer vision systems. In this paper we present the development of an object detection system to be useful while analyzing multispectral images. In this formulation general knowledge about spectral characteristics of the objects to be detected is utilized in the search for their location in an image. Efficiency of the system is derived by using a hierarchical framework with pyramid data structure to store multiresolution, multispectral copies of an image. At every level of processing a fuzzy cluster analysis algorithm is utilized to uncover the membership of individual picture elements. These membership values are used with the general knoweldge of spectral properties of objects to guide the search for their locations. The methodology is tested using several experiments involving multispectral satellite and aerial images. The system is shown to be successful in efficient detection of objects such as rivers, roads, and various types of buildings.