Image registration consists in estimating geometric and photometric transformations that align two images as best as possible. The direct approach consists in minimizing the discrepancy in the intensity or color of the pixels. The inverse compositional algorithm has been recently proposed for the direct estimation of groupwise geometric transformations. It is efficient in that it performs several computationally expensive calculations at a pre-computation phase. We propose the dual inverse compositional algorithm which deals with groupwise geometric and photometric transformations, the latter acting on the value of the pixels. Our algorithm preserves the efficient pre-computation based design of the original inverse compositional algorithm. Previous attempts at incorporating photometric transformations to the inverse compositional algorithm spoil this property. We demonstrate our algorithm on simulated and real data and show the improvement in computational efficiency compared to prev...