An improvement of the Canny edge based image expansion algorithm
Songze Zhang, Hongjian Shi · 2017
In this paper, an improvement of the Canny edge-based image expansion algorithm is proposed. Our new expansion algorithm preserves the edges of an object. It generates the higher contrast and sharper images through modification of the neighborhood pixel values of the edges. In this method, we define two cases according to the orientations of the edges. In any diagonal orientation, we define two new operators to determine whether the diagonal direction is the left or right diagonal. For different cases, we propose different functions to process the neighborhood pixel values of the edges. Finally, we compare the expansion results and analyze the resulted image contrasts from different expansion algorithms. Our proposed expansion method generates higher contrast and less blurring and zigzag images with crisper appearances.