  Photoreceptors in the retina are coupled by electrical synapses called "gap
junctions". It has long been established that gap junctions increase the
signal-to-noise ratio of photoreceptors. Inspired by electrically coupled
photoreceptors, we introduced a simple filter, the PR-filter, with only one
variable. On BSD68 dataset, PR-filter showed outstanding performance in SSIM
during blind denoising tasks. It also significantly improved the performance of
state-of-the-art convolutional neural network blind denosing on non-Gaussian
noise. The performance of keeping more details might be attributed to small
receptive field of the photoreceptors.
