Differential Evolution-based Approach for Tone-Mapping of High Dynamic Range Images

Recently, high dynamic range (HDR) imaging has received significant attention from research community as well as the industrial companies due to valuable applications of HDR images in better visualization and analysis. However, HDR images need to be converted to low dynamic range (LDR) images for viewing on standard LDR display screens. Several tone-mapping operators have been proposed for the conversion, however, so far, no significant works have been reported employing artificial intelligence to achieve better enhancement of the output images. In this paper, we present an optimization-based approach, to enhance the quality of the tone-mapped LDR images using metaheuristics. More specifically, the optimization process is based on the differential evolution (DE) algorithm which takes tone-mapping function of an existing histogram-based method as initial guess and refines the histogram bins iteratively leading to progressive enhancement of the quality of LDR image. The final results produced by the proposed optimized histogram-based approach (OHbA) showed better performance compared to the existing state-of-the-art tone-mapping algorithms.

@article{Almaghthawi2020,
  title     = {Differential Evolution-based Approach for Tone-Mapping of High Dynamic Range Images},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {7},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Ahmed Almaghthawi and Farid Bourennani and Ishtiaq Rasool Khan},
  doi       = {10.14569/IJACSA.2020.0110745},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110745}
}