Abstract
In this paper, we introduce a method and algorithm for resolution enhancement of low-resolution surface topography data by fusing them with corresponding high-resolution intensity images. This fusion is achieved by linking the three-dimensional topographical map to its intensity image via an intrinsic image-based shape-from-shading algorithm. Through computational simulation and physical experiments, the proposed method's effectiveness and repeatability have been evaluated, and the computational cost has been shown to be less than other state-of-the-art algorithms. This proposed method can be easily integrated with high-speed in-line measurements of high-dynamic-range surfaces.
Highlights
Products with functional surfaces have drawn wide attention in scientific research and engineering applications, including the areas of tribology, thermal conduction, hydrodynamic control, optics, solar energy, medical implantation, biomimetics, bioelectronics and microelectronics
The input low-resolution surface map was obtained from a low-pass filtered (Gaussian, with cut-off of 2.5 μm) version of the high-resolution surface map measured by a coherence scanning interferometry (CSI) [36]
By matching the CMM data to the stylus data using a scale-invariant feature transform (SIFT)based coarse matching, followed by an iterative-closest-points (ICP) fine matching, i.e. the SIFT-ICP algorithm [42,43], the height difference of corresponding points between the stylus data and CMM data was calculated
Summary
Products with functional surfaces have drawn wide attention in scientific research and engineering applications, including the areas of tribology, thermal conduction, hydrodynamic control, optics, solar energy, medical implantation, biomimetics, bioelectronics and microelectronics. We propose a fast resolution-enhancement method which can produce a high-resolution surface height map by fusing a low-resolution height map with its corresponding high-resolution intensity image, based on recently developed shape-fromshading techniques [20,21,22,23] With this solution, general sub-aperture 3D surface stitching can be replaced by fusing a global large-area low-resolution height map with several sub-aperture intensity images at different local regions, which are separately captured using a 3D sensor and 2D vision cameras. General sub-aperture 3D surface stitching can be replaced by fusing a global large-area low-resolution height map with several sub-aperture intensity images at different local regions, which are separately captured using a 3D sensor and 2D vision cameras This new approach can be significantly faster than sub-aperture stitching and many recently developed multi-sensor fusion techniques [24,25,26,27,28], which are used with coordinate data only. For review of general coordinate data fusion techniques, readers can refer elsewhere [29,30]
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