Code for the paper "Reflectance-guided, contrast-accumulated histogram equalization" published in ICASSP 2020.
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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.
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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.
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Requirements
- MATLAB
- Image processing toolbox (required for LIME)
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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.
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Please send any technical questions to the contact author, Xiaomeng Wu. You can get his email address by scanning the following QR code: