Super-high Dynamic Range Imaging

We propose a novel high dynamic range (HDR) imaging algorithm for the scenes that contain an extremely wide range of scene radiance. In the HDR imaging, several images are taken under different exposures. Those images usually have displacement from one another due to camera and/or object motions. The challenge of the super HDR imaging is to align those images because any image contains "lost" regions where texture information is completely lost due to overexposure or underexposure. We propose an image alignment algorithm based on similarities of region shapes instead of the similarities of the textures. Experimental comparisons demonstrate that the proposed algorithm outperforms state-of-the-art algorithms.