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- W4285134293 abstract "Summary We present how filters developed in the field of image processing can be efficiently applied to full waveform inversion, both in model and data space. These filters are known as Nonlinear Anisotropic Diffusion Filters (NADF). They rely on the solution of nonlinear diffusion partial differential equations (PDE), where the diffusion operator is a tensor. Basing this diffusion tensor on the image structure tensor, it is possible to design coherence enhancing filters, with the ability to smooth an input image only along identified structures, and not across them. This has a direct usage as a structure preserving smoothing operator, applicable to the gradient in full waveform inversion, with the advantage, over other structure preserving smoothing techniques, that the structure is detected automatically in the gradient, and does not depend on a prior information. NADF can also be used in the data space as a low-frequency enhancement technique. In this context, we show how the PDE formalism on which NADF are based makes it possible to introduce them as a general modification of the FWI misfit function, and how it can help mitigating cycle skipping in FWI. An illustration of both strategies is provided on a realistic synthetic example" @default.
- W4285134293 created "2022-07-14" @default.
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- W4285134293 date "2022-01-01" @default.
- W4285134293 modified "2023-09-30" @default.
- W4285134293 title "Nonlinear Anisotropic Diffusion Filters for FWI: Structure Preserving Smoothing and Data Low Frequency Enhancement" @default.
- W4285134293 doi "https://doi.org/10.3997/2214-4609.202210272" @default.
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