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Exposure Interpolation for Two Large-Exposure-Ratio Images

Existing multi-scale exposure fusion (MEF) algorithms which focus on defining weight maps to extract reliable information. However, they are difficult to preserve brightness order among over-exposed regions of a bright image and under-exposed regions of a dark image in a fused image when input images are two large-exposure-ratio images. In this paper, a new concept of exposure interpolation, which generates an appropriate bracketed sequence of virtual images from two input images, is introduced to address the problem. The possibly minimal number of virtual images is determined by using an optimization method. Then, an effective method by employing the intensity mapping function (IMF) is proposed to generate virtual images with proportional exposure times. The final image is produced by fusing both the two input images and the virtual images using multi-scale fusion. Experimental results show that the brightness order is preserved much better and the MEF-SSIM is significantly improved by the exposure interpolation.