An hybrid method for statistical multirate high-resolution signal reconstruction

Abstract

In this study, a hybrid method is proposed for the reconstruction of a high-resolution (HR) signal from a set of its noise corrupted low-resolution (LR) versions. In this hybrid method, noise reduction based on the empirical mode decomposition and Savitzky-Golay filtering is applied to the LR observations. Afterwards, zero-interpolated HR signals are obtained by performing up-sampling and time shifting on each LR signal. A one HR signal is produced by combining the zero-interpolated HR signals to a specified rule. To eliminate the ripple effect, finally, median filtering is applied to the resulting HR signal. As compared to the work employing Wiener filters, the proposed method comes into prominence as is it does not require any statistical information. It is demonstrated by simulation examples that the proposed method leads to satisfactory results in the reconstruction of HR signal.