  It is challenging to align multi-exposed images due to large illumination
variations, especially in presence of saturated regions. In this paper, a novel
image alignment algorithm is proposed to cope with the multi-exposed images
with saturated regions. Specifically, the multi-exposed images are first
normalized by using intensity mapping functions (IMFs) in consideration of
saturated pixels. Then, the normalized images are coded by using the local
binary pattern (LBP). Finally, the coded images are aligned by formulating an
optimization problem by using a differentiable Hamming distance. Experimental
results show that the proposed algorithm outperforms state-of-the-art alignment
methods for multi-exposed images in terms of alignment accuracy and robustness
to exposure values.
