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J. Imaging 2016, 2(3), 27; doi:10.3390/jimaging2030027

Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation

Mechatronics Engineering Technology, The Department of Engineering Technologies, Bowling Green State University, Bowling Green, OH 43402, USA
Academic Editor: Gonzalo Pajares Martinsanz
Received: 28 June 2016 / Revised: 2 September 2016 / Accepted: 8 September 2016 / Published: 15 September 2016
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Abstract

This article develops algorithms for the characterization and the visualization of micro-scale features using a small number of sample points, with the goal of mitigating the measurement shortcomings, which are often destructive or time consuming. The popular measurement techniques that are used in imaging of micro-surfaces include the 3D stylus or interferometric profilometry and Scanning Electron Microscopy (SEM), where both could represent the micro-surface characteristics in terms of 3D dimensional topology and greyscale image, respectively. Such images could be highly dense; therefore, traditional image processing techniques might be computationally expensive. We implement the algorithms in several case studies to rapidly examine the microscopic features of micro-surface of Microelectromechanical System (MEMS), and then we validate the results using a popular greyscale image; i.e., “Lenna” image. The contributions of this research include: First, development of local and global algorithm based on modified Thin Plate Spline (TPS) model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives using low resolution images. Second, development of a bending energy algorithm from our modified TPS model for filtering out image defects. Finally, development of a computationally efficient technique, referred to as Windowing, which combines TPS and Linear Sequential Estimation (LSE) methods, to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem. View Full-Text
Keywords: micro-surface imaging; evaluation; nondestructive; enhancement techniques; thin plate spline; linear sequential estimation; Windowing technique; Lenna image; MEMS imaging micro-surface imaging; evaluation; nondestructive; enhancement techniques; thin plate spline; linear sequential estimation; Windowing technique; Lenna image; MEMS imaging
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mayyas, M. Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation. J. Imaging 2016, 2, 27.

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