ExpoBlend: Information preserving exposure blending based on normalized log-domain entropy

In this paper, we present a solution to the problem of dynamic range compression from multiple exposures called ExpoBlend that operates in the absence of raw format images, relative or absolute exposure values, camera response functions, or known irradiance. This is achieved in relatively simplistic fashion by merging image content across provided exposures. The proposed algorithm is directed at making visible any contrast appearing across a dynamic range that exceeds display or printing capabilities through high dynamic range (HDR) compression while preserving the nature of the image structure and detail, lighting, and avoiding introducing discontinuities in illumination or image artifacts. In addition, ExpoBlend allows scaling subject to a single parameter that elicits a trade-off between the impact of illumination and fine detail in the merged result. The strategy applied appeals to an information maximization strategy wherein the local entropy evident in each exposure is computed subject to a logarithmic compression of intensities, and employs cross-exposure normalization of entropy that implies a fusion strategy based on relative entropy across exposures in combination with a soft-maximum operation.