Analysis of Multi-Component Non-Stationary Signals Using Fourier-Bessel Series and Wigner-Hough Transform

We presented a novel Fourier-Bessel（FB）series and Wigner-Hough transform（WHT） method for the analysis of multi-component non-stationary signals.The FB series decomposed multi-component nonstationary signals into mono-component signals. The Wigner-Ville distribution（WVD） was applied to each mono-component signal to analyze its time-frequency distribution（TFD）. Summing up the WVDs of the individual components resulted in TFDs of the multicomponent signals, where the cross terms and noise were significantly reduced. The Hough transform（HT）was applied on the TFD of the multi-component signal（obtained from FB-WVD）. The HT provides an important tool for mapping the signals onto a parameter space where the detection and estimation problems are made easier. This mapping can be used in the detection and parameter estimation of signals which are unknown and embedded in noise.

3D image reconstruction with a controllable overlapping number of elemental images in computational integral imaging

In this Letter, we propose a three-dimensional （3D） image reconstruction method with a controllable overlapping number of elemental images in computational integral imaging. The proposed method can control the overlap- ping number of pixels coming from the elemental images by using the subpixel distance based on ray optics between a 3D object and an image sensor. The use of a controllable overlapping number enables us to provide an improved 3D image visualization by controlling the inter-pixel interference within the reconstructed pixels. To find the optimal overlapping number, we simulate the pickup and reconstruction processes and utilize the numerical reconstruction results using a peak signal-to-noise ratio （PSNR） metric. To demonstrate the feasibility of our work in optical experiments, we carry out the preliminary experiments and present the results.