Non Local Means (NLM) filtering is a well-known image-processing algorithm for random noise attenuation. It is based on the assumption that coherent and non-coherent features can be identified and separated using a measure of similarity between adjacent samples. In this paper we review and extend previous work on the use of NLM in seismic data processing. Our objective is to improve the computational efficiency of the method and investigate practical aspects of its implementation and application. Synthetic and real data examples demonstrate the achieved improvements.

Practical Aspects of Non Local Means Filtering of Seismic Data

De Gaetani, C. I.;
2016

Abstract

Non Local Means (NLM) filtering is a well-known image-processing algorithm for random noise attenuation. It is based on the assumption that coherent and non-coherent features can be identified and separated using a measure of similarity between adjacent samples. In this paper we review and extend previous work on the use of NLM in seismic data processing. Our objective is to improve the computational efficiency of the method and investigate practical aspects of its implementation and application. Synthetic and real data examples demonstrate the achieved improvements.
atti del convegno: "78th EAGE Conference and Exhibition 2016: Efficient Use of Technology - Unlocking Potential"
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1048741
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