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Separation of blended data by iterative estimation and subtraction of interference noise
Author(s) -
P. Doulgeris,
A. Mahdad,
Gerrit Blacquière
Publication year - 2010
Publication title -
research repository (delft university of technology)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1190/1.3513579
Subject(s) - noise (video) , computer science , separation (statistics) , interference (communication) , subtraction , iterative method , source separation , background subtraction , artificial intelligence , algorithm , mathematics , telecommunications , machine learning , arithmetic , channel (broadcasting) , image (mathematics) , pixel
Conventional data acquisition practice dictates the existence of sufficient time intervals between the firing of successive sources in the field. However, much attention has been drawn recently to the possibility of shooting in an overlapping fashion. Numerous publications have addressed the issue from different scopes (denoising, compressing, blind signal separation etc.) while others have defined the theoretical background. The term ‘blending’ was introduced to describe this new trend in acquisition designs, the time-overlapping data acquisition. In turn, the term ‘deblending’ refers to an algorithm that recovers the data as if they were shot in the conventional way. Such an algorithm is presented in this chapter for application on both impulsive and vibrating sources. This algorithm is based on iterative interference estimation and subtraction and is applied to field data.

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