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- W2517502436 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." @default.
- W2517502436 created "2016-09-16" @default.
- W2517502436 creator A5009196548 @default.
- W2517502436 date "2016-08-27" @default.
- W2517502436 modified "2023-09-26" @default.
- W2517502436 title "Image Reconstruction and Evaluation of Micro-surfaces for MEMS Application" @default.
- W2517502436 doi "https://doi.org/10.20944/preprints201608.0218.v1" @default.
- W2517502436 hasPublicationYear "2016" @default.
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