Doctor of Philosophy

dissertationWhile boundary representations, such as nonuniform rational B-spline (NURBS) surfaces, have traditionally well served the needs of the modeling community, they have not seen widespread adoption among the wider engineering discipline. There is a common perception that NURBS are slow to evaluate and complex to implement. Whereas computer-aided design commonly deals with surfaces, the engineering community must deal with materials that have thickness. Traditional visualization techniques have avoided NURBS, and there has been little cross-talk between the rich spline approximation community and the larger engineering field. Recently there has been a strong desire to marry the modeling and analysis phases of the iterative design cycle, be it in car design, turbulent flow simulation around an airfoil, or lighting design. Research has demonstrated that employing a single representation throughout the cycle has key advantages. Furthermore, novel manufacturing techniques employing heterogeneous materials require the introduction of volumetric modeling representations. There is little question that fields such as scientific visualization and mechanical engineering could benefit from the powerful approximation properties of splines. In this dissertation, we remove several hurdles to the application of NURBS to problems in engineering and demonstrate how their unique properties can be leveraged to solve problems of interest

COMPRESSIVE IMAGING AND DUAL MOIRE´ LASER INTERFEROMETER AS METROLOGY TOOLS

Metrology is the science of measurement and deals with measuring different physical aspects of objects. In this research the focus has been on two basic problems that metrologists encounter. The first problem is the trade-off between the range of measurement and the corresponding resolution; measurement of physical parameters of a large object or scene accompanies by losing detailed information about small regions of the object. Indeed, instruments and techniques that perform coarse measurements are different from those that make fine measurements. This problem persists in the field of surface metrology, which deals with accurate measurement and detailed analysis of surfaces. For example, laser interferometry is used for fine measurement (in nanometer scale) while to measure the form of in object, which lies in the field of coarse measurement, a different technique like moire technique is used. We introduced a new technique to combine measurement from instruments with better resolution and smaller measurement range with those with coarser resolution and larger measurement range. We first measure the form of the object with coarse measurement techniques and then make some fine measurement for features in regions of interest. The second problem is the measurement conditions that lead to difficulties in measurement. These conditions include low light condition, large range of intensity variation, hyperspectral measurement, etc. Under low light condition there is not enough light for detector to detect light from object, which results in poor measurements. Large range of intensity variation results in a measurement with some saturated regions on the camera as well as some dark regions. We use compressive sampling based imaging systems to address these problems. Single pixel compressive imaging uses a single detector instead of array of detectors and reconstructs a complete image after several measurements. In this research we examined compressive imaging for different applications including low light imaging, high dynamic range imaging and hyperspectral imaging