  Existing image enhancement methods fall short of expectations because with
them it is difficult to improve global and local image contrast simultaneously.
To address this problem, we propose a histogram equalization-based method that
adapts to the data-dependent requirements of brightness enhancement and
improves the visibility of details without losing the global contrast. This
method incorporates the spatial information provided by image context in
density estimation for discriminative histogram equalization. To minimize the
adverse effect of non-uniform illumination, we propose defining spatial
information on the basis of image reflectance estimated with edge preserving
smoothing. Our method works particularly well for determining how the
background brightness should be adaptively adjusted and for revealing useful
image details hidden in the dark.
