We present an approach to perform automatic target detection of small targets from coregistered visual, thermal, and range images, using five features of value for target discrimination: Brightness, Texture, Temperature, Surface Planarity, and Height. For each, we proposed a set of operations to extract targets from the images, using inherent target properties that differentiate them from clutter. Each of the target extractors yields a `Target Measure' image, based on a specific feature. These, when combined appropriately, yield better results than those obtained by individual, single image detectors. Two methods are presented to perform information fusion on the target measure images: Binary Combination and Fuzzy Combination. Experimental results using both combination methods on synthetic and real imagery are given with very satisfactory results. A morphological operation called `erosion of strength n' is introduced and utilized as a powerful tool for removal of spurious information in binary images.