Fusion of Multi-view Multi-exposure Images with Delaunay Triangulation

In this paper, we present a completely automatic method for multi-view multi-exposure image fusion. The technique adopts the normalized cross-correlation (NCC) as the measurement of the similarity of interest points. With the matched feature points, we divide images into a set of triangles by Delaunay triangulation. Then we apply affine transformation to each matched triangle pairs respectively to get the registration of multi-view images. After images aligned, we partition the image domain into uniformed regions and select the images that provides the most information with certain blocks. The selected images are fused together under monotonically blending functions.