The Intrinsic Error of Exposure Fusion for HDR Imaging, and a Way to Reduce it

TitleThe Intrinsic Error of Exposure Fusion for HDR Imaging, and a Way to Reduce it
Publication TypeConference Paper
Year of Publication2015
AuthorsRodríguez RGil, Vazquez-Corral J, Bertalmío M
Conference NameBritish Machine Vision Conference (BMVC)
In this paper we present a novel approach to the problem of exposure fusion of a stack of pictures for the generation of high dynamic range (HDR) radiance maps. All
exposure fusion approaches, when applied on 8-bit non-RAW pictures, perform photometric calibration by estimating and inverting the camera response function, which is assumed to be a channelwise-independent function which does not change with the exposure. Our experiments show that these assumptions do not always hold and that the camera may automatically introduce changes (in gain, white balance, gamma correction value) from one exposure to the next when performing the non-linear operations involved in recording pictures in non-RAW formats such as JPEG. The net result is that HDR radiance maps obtained from exposure fusion of non-linear data may have substantially more error than if computed directly from the linear, RAW data. Our proposed method overcomes this problem and compensates for the changes introduced by the camera by matching the color correction and gamma correction transforms of all pictures to those of a reference picture in the stack, providing a clear improvement in terms of PSNR with respect to the classical method of Debevec and Malik.