computational theory of vision

The computational theory of vision suggests that the brain processes visual information through specific algorithms or steps, much like a computer, to interpret what we see. It proposes that the brain extracts features from visual input—such as edges, shapes, and patterns—and systematically integrates this data to recognize objects, depth, and movement. This approach models vision as a series of problem-solving processes, aiming to understand how complex visual scenes are efficiently analyzed and understood by the brain, combining biological insights with computational principles to explain visual perception.