Noise Reduction Algorithm Based on Complex Wavelet Transform of Digital Gamma Ray Spectroscopy

This paper investigates the use of complex wavelets in gamma ray spectroscopy signals. In this paper an algorithm for noise elimination of the detected gamma ray spectroscopy signals is studied. This algorithm is based on the complex wavelet transform. Reconstruction of the original detected signal is obtained by applying the inverse complex wavelet transform to the transformed complex wavelet transform signal. Five different cases are studied with different five levels of the complex wavelet transform. Consequently, comparisons between these levels are considered in terms of maximum number of peak heights, execution time, and peak signal to noise ratio (PSNR). Moreover, comparison between different signal reconstruction with respect to different complex wavelet transform levels, size of the transformed signal in each level, and number of coefficient in each subband for certain level. One of the main advantages of this algorithm that discussed in the previous literature is that its filters do not have serious distributed bumps in the wrong side of the power spectrum and, simultaneously, they do not introduce any redundancy to the original signal. The obtained result confirms the high accuracy of the considered algorithm over traditional algorithms for both noise elimination and signal reconstruction.