Consider an $N$-dimensional space $\mathcal H$. Two orthonormal bases $\newcommand{\ket}[1]{\lvert #1\rangle}\{\ket{u_j}\}_{j=1}^N,\{\ket{v_j}\}_{j=1}^N\subset\mathcal H$ are said to be Mutually Unbiased Bases (MUBs) if $\lvert\langle u_i\lvert v_j\rangle\rvert =1/\sqrt N$ for all $i,j$.
Suppose we want to fully reconstruct a state $\rho$ by means of projective measurements. A single basis provides us with $N-1$ real parameters (the $N$ outcome probabilities associated with the measurement, minus one for the normalisation constraint).
Intuitively, if two bases are mutually unbiased, they provide fully uncorrelated information (finding a state in some $\ket{u_j}$ says nothing about which $\ket{v_k}$ would have been found), and thus measuring the probabilities in two different MUBs should characterise $2(N-1)$ real parameters. If we can measure in $N+1$ different MUBs (assuming they exist), it thus stands to reason that we characterised $(N-1)(N+1)=N^2-1$ independent real parameters of the state, and thus obtained tomographically complete information. This is also mentioned in passing in this paper (page 2, second column, arXiv:0808.0944).
What is a more rigorous way to see why this is the case?