Multiscale anisotropic diffusion for ringing artifact suppression in geophysical deconvolution data

Abstract

Ringing artifact degradations always appear in the deconvolution of geophysical data. To address this problem, we propose a postprocessing approach to suppress ringing artifacts that uses a novel anisotropic diffusion based on a stationary wavelet transform (SWT) algorithm. In this paper, we discuss the ringing artifact suppression problem and analyze the characteristics of the deconvolution ringing artifact. The deconvolution data containing ringing artifacts are decomposed into different SWT subbands for analysis, and a new multiscale adaptive anisotropic filter is developed to suppress these degradations. Finally, we demonstrate the performance of the proposed method and describe the experiments in detail.

Investigation of Deconvolution Method with Adaptive Point Spread Function Based on Scintillator Thickness in Wavelet Domain

“…First, when performing sharpness improvement for each sub-band, artifacts may increase, similar to the deconvolution process. Deconvolution algorithms create ringing artifacts because errors often cause strong oscillations at data discontinuities, such as edges and noise, sometimes manifesting as false edges [37]. These artifacts can distort inverse DWT images; however, if these factors are not sufficiently reflected in the SSIM and GM evaluation values, the proposed algorithm may find it difficult to derive the optimal parameters.…”

“…These artifacts can distort inverse DWT images; however, if these factors are not sufficiently reflected in the SSIM and GM evaluation values, the proposed algorithm may find it difficult to derive the optimal parameters. To address this issue, a method that reduces ringing artifacts through diffusion filters [37] or PSF frequency analysis [38] can be considered as a solution. Further research is planned for the future.…”

New Methods for Data Stacking and P‐ and S‐wave Arrival Time Determination Using the Deep Moonquake Apollo Recordings

“…We note that these processing steps are motivated by the need to use the data in stacking and correlating algorithms which would otherwise be dominated by the spikes and signals outside the frequency window of interest. The sensors at all four Apollo sites are the same, so instrument deconvolution which, depending on method, can introduce ringing (Zuo et al, 2016), as with many previous lunar studies, was not done. Example of LP APSE lunar data for the three components from Station 15 for a deep moonquake (August 04, 1971, from 07:05:00 to 07:45:00) in Cluster A1.…”