Exposure-Robust Alignment of Differently Exposed Images

This letter presents a novel exposure-robust method to align differently exposed images. First, a directional mapping approach is introduced to normalize differently exposed images so as to alleviate the effect of saturation. Then, a non-parametric local binary pattern (LBP) is employed to represent intensity-invariant features of these images. An efficient two-stage alignment is proposed for motion estimation. Experiments on a variety of synthesized and real image sequences demonstrate that the proposed method is less sensitive to the reference image, and robust to 12 exposure values (EV) increments, which is superior to existing methods.