Quality control of micro-nano structured and freeform surfaces is becoming increasingly important, which leads to challenging requirements in the measurement and characterization of rough and highly reflective surfaces. As an important measurement technique, white light scanning interferometry (WLSI) is a fast noncontact method to measure three-dimensional (3D) surface profiles. Nevertheless, the existing WLSI 3D surface reconstruction algorithms are prone to environmental vibrations and phase changes caused by reflections on the tested surface. A novel peak detecting algorithm that combines the white light phase-shifting interferometry (WLPSI) method and fast Fourier transform (FFT) coherence-peak-sensing technique is proposed in this paper, which can accurately determine the local fringe peak and improve the vertical resolution of the measurement. A microcomponent (10 μm standard step height) and a spherical surface were used as test specimens to evaluate the proposed method. Both simulated and experimental results show that the proposed algorithm improves the precision and anti-interference ability of the WLPSI and FFT methods, which can effectively reduce the batwing effects at the edges and solve the problem of positioning error in the maximum modulation.

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Compressive sensing (CS) theory has great potential for reconstructing CT images from sparse-views projection data. Currently, total variation (TV-) based CT reconstruction method is a hot research point in medical CT field, which uses the gradient operator as the sparse representation approach during the iteration process. However, the images reconstructed by this method often suffer the smoothing problem; to improve the quality of reconstructed images, this paper proposed a hybrid reconstruction method combining TV and non-aliasing Contourlet transform (NACT) and using the Split-Bregman method to solve the optimization problem. Finally, the simulation results show that the proposed algorithm can reconstruct high-quality CT images from few-views projection using less iteration numbers, which is more effective in suppressing noise and artefacts than algebraic reconstruction technique (ART) and TV-based reconstruction method.

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