Region-of-Interest Estimation for Adaptive Resource Allocation in Multi-Aperture Imaging Systems

Successful design of a flat-profile multiplexed optical imaging system requires the use of adaptive techniques to make intelligent resource allocation based on the information content in the imaging system´s field-of-view. This paper explores techniques for finding regions of interest in aerial images using local entropy as a descriptor. A novel method for identifying regions-of-interest in images is developed using the 2D normalized power spectral density within Gilles´ saliency map estimator. Application of the method to candidate aerial images shows its ability to identify consistent regions of interest for such data for varying block sizes and under additive noise.