Research on seismic data denoising method based on K-SVD algorithm
DeShu Lin, CaiFeng Cheng · 2024
In data processing, the removal of random noise is an essential step in order to improve quality. This article presents a detailed study on the removal of random noise in seismic signals, aiming to seek a more efficient and practical denoising method. This paper proposes a seismic data denoising method based on the K-SVD algorithm. By performing sparse decomposition and dictionary learning on seismic signals, the method achieves effective denoising of seismic signals. The results show that this method has a good denoising effect on seismic data.