Although the properties of the human visual system have been studied extensively, the knowledge of its operations are usually considered only for comparison, and models based on its function are rarely utilized. Complexity and speed of computation are often the most quoted reasons for choosing not to implement such models. Nonetheless, if we are to achieve the flexibility and power of the biological visual system, researchers would be wise to continue to explore practical, yet comprehensive models based on human vision. This paper examines the first stage of the primate visual system, the retina, and how simple models of its neurons, along with their properties and interactions, can mimic what is presently believed to be some of the initial forms of visual image processing. A static model based on the previously explored ideas of shunting dynamics will be presented along with the introduction of image (photoreceptor) blurring, driven by feedback from the shunting network. Simulations are used to demonstrate the model.