  A channel should be built to transmit information from one place to another.
Imaging is 2 or higher dimensional information communication. Conventionally,
an imaging channel comprises a lens and free spaces of its both sides. The
transfer function of each part is known; thus, the response of a conventional
imaging channel is known as well. Replacing the lens with a scattering layer,
the image can still be extracted from the detection plane. That is to say, the
scattering medium reconstructs the channel for imaging. Aided by deep learning,
we find that different from the lens there are different channels in a
scattering medium, i.e., the same scattering medium can construct different
channels to match different manners of source encoding. Moreover, we found that
without a valid channel the convolution law for a shift-invariant system, i.e.,
the output is the convolution of its point spread function (PSF) and the input
object, is broken, and information cannot be transmitted onto the detection
plane. In other words, valid channels are essential to transmit image
information through even a shift-invariant system.
