Bi-lateral filtering based edge detection on hexagonal architecture
Edge detection plays an important role in image processing but is still an open problem. This paper presents a novel edge detection method based on bi-lateral filtering which achieves better performance than single Gaussian filtering. In this form of filtering, both spatial closeness and intensity similarity of pixels are considered in order to preserve important visual cues provided by edges and reduce the sharpness of transitions in intensity values as well. In addition, the edge detection method proposed in this paper is achieved on hexagonally sampled images. Due to the compact and circular nature of the hexagonal lattice, a better quality edge map is obtained on hexagonal architecture than common edge detection on square architecture. Experimental results using our proposed method in this paper exhibit encouraging performance.