The Application of Lateral Inhibition Model in Image's Contour Enhancement and Design of Its Electro-Model

For overcoming the problems such as distortion and shift of object’s edge, easily losing the object detail information of methods in image edge detection, and satisfying higher demand for object detection in the modern war, a new image edge detection method was designed. LOG edge detection as a typical image processing method was introduced and the disadvantage of this model was analyzed firstly. Based on lateral inhibition theory, an acyclic lateral inhibition network model (ALINM) based on biology vision information processing mechanism was designed. The feasibility of object detection by lateral inhibition model was analyzed, in order to express the advantage such as rapid calculation easily real time operation of ALINM, the calculation magnitude of circulation difference lateral inhibition model was analyzed. Besides the correctness of ALINM was confirmed with two input cells, its transfer function was deduced. An algorithm of image edge detection based on this model was established finally, lateral inhibition effect also was confirmed by one-dimension and two-dimension circuit model based ALINM. Simulative experiment with different parameters and physics experiment prove that acyclic lateral inhibition network model can be realized easily, it can preserve the farthest detail information of object and has faster calculation speed than LOG operator. ALINM and lateral inhibition theory provide a useful method based on biology vision for object detection under difficult imaging conditions.