  In dark channel based methods, local constant assumption is widely used to
make the algorithms invertible. It inevitably introduces defects since the
assumption can not perfectly avoid depth discontinuities and meanwhile cover
enough pixels. Unfortunately, because of the limitation of the prior, which
only confirms the existence of dark things but does not specify their locations
or likelihood, no fidelity measurement is available in refinement thus the
defects are either under-corrected or over-corrected. In this paper, we go
deeper than the dark channel theory to overcome this problem. We split the
concept of dark channel into dark pixels and local constant assumption, and
then, control the problematic assumption based on a novel weight map. With such
effort, our methods show significant improvement on quality and have
competitive speed. In the last, we show that the method is highly robust to
initial transmission estimates and can be ever-improved by providing better
dark pixel locations.
