Multi-Scale Recognition of Objects Approach based on Inherent Redundancy Information Entropy Equalization

Development of new imaging sensors arise the need for image processing techniques that can effectively fuse images from different sensors into a single coherent composition for interpretation. In order to make use of inherent redundancy and extended coverage of multiple sensors, we propose a multiscale approach for pixel level image fusion. The ultimate goal is to reduce human/machine error in detection and recognition of objects. The simulation results show that the proposed algorithm has increased the rate of object detection.