Avoid saturated pixels in cross-correlation computation
I have finally found an aswer in a technical report "Image Alignment and Stitching: A Tutorial" from Richard Szeliski.

A weighted SSD (Sum of Suqared Differences) function is presented on page 13:

$$E_{WSSD}(u)=\sum_{i}w_{0}(x)w_{1}(x_{i}+u)\left[I_{1}(x_{i}+u)-I_{0}(x_{i})\right]^{2}$$

where $w_{0},w_{1}$ are spatially-varying weight functions (for template and the image). $u$ is a template offset.

The result may be divided by the overlap area to avoid bias towards smaller overlap.

This however works for SSD metric, not NCC. But it may suffice once images are normalized beforehand (using contrast/brightness adjustment computed using linear regression over corresponding pixel intensities).