| One of the functions of the visual periphery is that it filters out irrelevant information and enhances important information, such as edges. The eye is capable of detecting changes in light illuminance in both space, and time. In space, these changes are termed spatial edges, and in time, they might be termed off-on steps of stimulus.; Many models of the visual periphery either focus on spatial edges or temporal edges. I propose a biologically-inspired neural network model, the Edgetron, that detects both the spatial and temporal components of visual it examines pertinent features of the visual periphery that are common across all species. This model will be quantitatively verified according to existing experimental results and observations. It will be shown how the Edgetron can applied to address the compression/video quality tradeoff involved with the design of a MPEG-based encoder. |
