Many image grey level thresholding methods based on the theory of maximum entropy have been proposed in the past. However, the exact definition of what is meant by 'image entropy' has varied considerably, with measures based on the image itself, its histogram or other related distributions being proposed. Most of these ignore the spatial component of the image, assuming pixels within the image to be independent of each other. While this is convenient, it is counterintuitive. A recent measure of spatial entropy, which attempts to include the spatial information inherent in the image, has been used here as a criterion function for threshold selection. Results indicate an improvement over methods that ignore this information.