Superpixel Based Patch Match For Differently Exposed Images With Moving Objects And Camera Movements

A challenging problem for high dynamic range (HDR) imaging is to reconstruct a ghosting-free HDR image for an HDR scene with moving objects. In this paper, a superpixel based patch match algorithm is proposed to synchronize differently exposed images with moving objects and camera movements according to a selected reference image. The concept of superpixel is adopted to divide the reference image into atomic regions, and a new bilateral weight is introduced for the computation of matching cost to reduce outliers. All the input images are synchronized by using the estimated optical flow. The synchronized images are further refined via a weighted guided image filter with the reference image as the guidance image. Experimental results show that the proposed algorithm can remove the scene variations in the presence of moving objects and camera movements. A ghost-free HDR image can then be reconstructed for differently exposed images with moving objects and camera movement by using an existing exposure fusion algorithm.