I am working on a project that employs a linear array sensor that provides data from the same object at two different energies. Collected in time, I end up with two images (16-bit sensor values, MxM image), call one HIGH the other LOW. My engineering background is Material Science and metallurgy, so I am coming up to speed on DSP, image analysis, and all of the bits that bring all of that together.
I have been researching "image fusion" and have been working from Gonzalez's fabulous Digital Image Processing (3rd ed.) text. I have developed an understanding of DWT and have successfully written code to replicate the 3-scale DWT transforms in the text (major accomplishment for me).
Now, I am trying to understand how to "fuse" the DWT coefficients from the LOW and HIGH images. From the IEEE Xplore database, I pulled several papers on the topic; one of the more useful is by Zhiyu Chen, et.al. "A Combinational Approach to the Fusion, De-noising and Enhancement of Dual-Energy X-Ray Luggage Images".
Succinctly, they recommend "averaging the corresponding approximation coefficients of L and H" (sigma)... and "summing the corresponding detail coefficients of L and H" (psi). But, that is all of what is said on the matter.
I have several other sources, but they must presume some obvious bit of understanding that I am lacking!
My question is, in order to successfully fuse the HIGH and LOW images: what does this mean? In the case of a 3-scale DWT, do I average or sum the 3-rd scale approximation/detail coefficients? Do I somehow average across each scale, despite the fact that the size of the coefficient matrices are different by powers of 2?