Method of image fusion and enhancement using mask pyramid

Image fusion is an important visualization technique of integrating coherent spatial and temporal information into a compact form. Laplacian fusion is a process that combines regions of images from different sources into a single fused image based on a salience selection rule for each region. In this paper, we proposed an algorithmic approach using a mask pyramid to better localize the selection process. A mask pyramid operates in different scales of the image to improve the fused image quality beyond a global selection rule. Several examples of this mask pyramid method are provided to demonstrate its performance in a variety of applications. A new embedded system architecture that builds upon the Acadia® II Vision Processor is proposed.