Model-based region-of-interest estimation for adaptive resource allocation in multi-aperture imaging systems

Using intelligent resource allocation based on the information content in the imaging system´s field-of-view for the successful design of a flat-profile multiplexed optical imaging system requires the use of adaptive techniques. This paper describes a model-based technique for determining regions of interest in aerial images using the 2D normalized power spectral density within Gilles´ saliency map estimator. The proposed technique exploits the 1/f^alpha spatial spectral shape of such natural imagery in a computationally-simple approach that is robust to additive noise. Application of the method to candidate aerial images shows its ability to identify consistent regions of interest for such data.