Color Mapping Functions For HDR Panorama Imaging: Weighted Histogram Averaging

It is challenging to stitch multiple images with different exposures due to possible color distortion and loss of details in the brightest and darkest regions of input images. In this paper, a novel color mapping algorithm is first proposed by introducing a new concept of weighted histogram averaging (WHA). The proposed WHA algorithm leverages the correspondence between the histogram bins of two images which are built up by using the non-decreasing property of the color mapping functions (CMFs). The WHA algorithm is then adopted to synthesize a set of differently exposed panorama images. The intermediate panorama images are finally fused via a state-of-the-art multi-scale exposure fusion (MEF) algorithm to produce the final panorama image. Extensive experiments indicate that the proposed WHA algorithm significantly surpasses the related state-of-the-art color mapping methods. The proposed high dynamic range (HDR) stitching algorithm based on MEF also preserves details in the brightest and darkest regions of the input images well. The related materials will be publicly accessible at https://github.com/yilun-xu/WHA for reproducible research.