Article
Version 1
Preserved in Portico This version is not peer-reviewed
Image Reconstruction and Evaluation of Micro-surfaces for MEMS Application
Version 1
: Received: 27 August 2016 / Approved: 27 August 2016 / Online: 27 August 2016 (10:43:36 CEST)
A peer-reviewed article of this Preprint also exists.
Mayyas, M. Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation. J. Imaging 2016, 2, 27. Mayyas, M. Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation. J. Imaging 2016, 2, 27.
Abstract
This article develops algorithms for the characterization and the visualization of micro-scale features by using a small number of sample points, and with a goal to mitigate for the measurement shortcomings which are often destructive or time consuming. We implement the algorithms to rapidly examine the microscopic features of a Microelectromechanical System (MEMS) surface. Such images are highly dense; therefore, traditional image processing techniques might be computationally expensive. The contribution of this research include first, we develop 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 by using low resolution images. Second, we obtain a bending energy algorithm from our modified TPS model, and use it to filter out image defects. Finally, we develop a computationally efficient Windowing technique, which combines TPS and Linear Sequential Estimation (LSE), to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.
Keywords
micro-surface imaging; evaluation; nondestructive; enhancement techniques; thin plate spline; linear sequential estimation; windowing technique, Lenna image, MEMS imaging
Subject
Engineering, Control and Systems Engineering
Copyright: 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.
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