Radiance map construction based on spatial and intensity correlations between LE and SE images for HDR imaging

2016 
HDR image was developed for the reproduction of real scenes with an acquisition of large dynamic range. In general, HDR image consists of several different exposure images according to the exposure value of a digital camera. Before the construction of a single HDR image, each input image is calibrated using CRF to convert its image data to scene radiance. In order find CRF, conventional methods require special apparatus and reference targets, or several exposure images. This paper proposes a new HDR blending algorithm that uses only dual-exposure images. The proposed algorithm is based on the least squares method, and includes spatial and intensity weighting functions. Each weighting function is used to reduce error points and improve CRF computation accuracy. In addition, a constraint is added to correct white balance in the brightness level. The rendering results show that the proposed algorithm is superior to the conventional algorithm.
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