Multi-scale image fusion using the Parameterized Logarithmic Image Processing model

Image fusion is the process of combining multiple images into a single image which retains the most pertinent information from each original image source. More recently, multi-scale image fusion approaches have emerged as a means of providing a more meaningful fusion which better reflects the human visual system. In this paper, multi-scale decomposition techniques and image fusion algorithms are adapted using the Parameterized Logarithmic Image Processing (PLIP) model, a nonlinear image processing framework which more accurately processes images. Experimental results via computer simulations illustrate the improved performance of the proposed algorithms by both qualitative and quantitative means.