How to combine normxcorr2 similarity results with single value, like mutual information?

Hi everyone

I want a single value normalized cross-correlation similarity between two images while transforming. This value I want to compare with other similarity measures, such as mutual information.

 for i = 50:step:end_rang
            % horizantal transformation
            [overlap_fix,overlap_float] = overlapArea(fix_img,float_img,i);
            MI(2,ind) = size(overlap_fix,2);
            MI(3,ind)   = MutualInfo(overlap_fix,overlap_float,all_float_px,overlap_limit);
            JD(ind)     = jeffrey_divergence_Xu_paper(overlap_fix,overlap_float,all_float_px,overlap_limit);
            if std(double(overlap_fix(:))) ~= 0
                cc(ind) = sum(sum(normxcorr2(overlap_fix,overlap_float)))/numel(overlap_fix);
            else
                cc(ind) = 0;
                disp(['skip ',num2str(i)]);
            end
            ind = ind +1;
        end

The method I use to convert 'normxcorr2' output matrix to a single value, is it correct? where the identical images have the highest value