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Code for the paper "Reflectance-guided, contrast-accumulated histogram equalization" published in ICASSP 2020.

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Code for the paper "Reflectance-guided, contrast-accumulated histogram equalization" published in ICASSP 2020.

  • In this paper, we have proposed a histogram equalization-based image enhancement method that adapts to the data-dependent requirements of brightness enhancement and improves visibility of details without losing global contrast.

  • Please read LICENSE.md for more information on licenses.

  • The original code was tested with MATLAB R2017b on a machine running CentOS 6.5, but it should work on other OSs as well.

  • Requirements

    • MATLAB
    • Image processing toolbox (required for LIME)
  • Run mex ContrastAccumulatedHistogram.c to build the mex function

  • Run demo.m to see an example of image enhancement.

  • LIME.p is provided by Guo et al., and used as an edge-preserving filter for illumination estimation.

  • Test images are provided by USC-SIPI and Guo et al.

  • Please send any technical questions to the contact author, Xiaomeng Wu. You can get his email address by scanning the following QR code:

    qr

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Code for the paper "Reflectance-guided, contrast-accumulated histogram equalization" published in ICASSP 2020.

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