Multi-scale edge detection with dominating opponent inhibition

Noise suppression conflicts with high accuracy in image edge detection. A multi-scale edge detection model with dominating opponent inhibition was proposed from physiological point of view. The presented model made extension of dominating opponent inhibition mechanism to processing at multiple scales. Image noise can be adaptively suppressed by dominating inhibition from the opponent path of lateral geniculate nucleus. Sharp edges were obtained through the non-linear combination of simple cell subfields. Finally multi-scale processing results were combined to obtain boundary contour. Theoretical analysis and experimental results indicate that the proposed model performs well in noise suppression and accurate edge detection through the combination of dominating opponent inhibition and multi-scale processing. Meanwhile, it is biologically plausible, simple and efficient.