Some time ago I remember reading about how the human brain breaks down visual information into a number of individual channels.For example, one channel might focus on edges and lines, another might focus on being a contrast map, while another provide a color information overlay. Each channel being a much more simplified part of the entire visual input.From what I understood, modern research into the visual cortex has provided some insight into what the channels might be and how they're broken down. If my understanding of current research is correct I was hoping to find some more detailed information explaining how the visual information is broken down and processed (articles at the technical level of Scientific American are fine, so long as they detail the types of channels present).My desired take-away from this is to brainstorm ideas for how I might better pre-process an image into feature data for a standard neural network learning algorithm, based on the human experience.
How does the brain break down visual information for processing? What channels is visual input broken into?
vision;neural network