Image fusion and enhancement using triangulated irregular networks

A triangulated irregular network (TIN) is a viable structure for vector representation of raster image data. To visualize the image characterized by triangulation, it is required to fit a continuous surface of pixel brightness values in the triangulation (i.e. to interpolate data stored in its vertices). From this perspective, this paper presents a multi-frame image fusion and enhancement process that employs TIN structures rather than arrays of pixels as the original working units. The feasibility of this application relates to the fact that a TIN model offers a good quality digital image representation with a reduced density of pixel values as compared to a corresponding raster representation [4]. In the proposed process several low-resolution unregistered and compressed images (such as those extracted from a video footage) of a common scene are: (a) registered to a sub-pixel level (b) transformed to a TIN structure, (c) grouped or mapped globally within a singular framework to create a denser TIN composite, and (d) the TIN representation is used in reverse to reconstruct a higher resolution image in raster format with more details than any of the original input frames. Tests and subsequent results are shown to demonstrate the validity and accuracy of the proposed multi-frame image enhancement process. A comparison of this process of multi-frame image enhancement using various interpolation methods and practices is included.