Dictionary learning noise
WebApr 5, 2024 · Seismic wave acquisition is usually disturbed by natural noise and instrument noise. As the seismic wave propagates, the filtering effect of the Earth and its various layers will result in energy attenuation and velocity dispersion; these phenomena weaken the seismic time series amplitudes and distort the seismic phase data. In traditional … WebJan 14, 2024 · Since the concept of dictionary learning is a well-defined analytical solution for vector space encoding, the concept of dictionary learning is used from purely …
Dictionary learning noise
Did you know?
WebThe convolutional dictionary learning has the advantage of the shift-invariant property. The deep convolutional dictionary learning algorithm (DCDicL) combines deep learning … WebDec 9, 2024 · Here, we develop an automatic method to attenuate coherent noise based on the adaptive dictionary learning algorithm. The adaptive dictionary algorithm can learn …
WebFeb 18, 2024 · Dictionary learning has been demonstrated to be efficient for various noise removal. Aharon and Elad [ 33, 34] proposed the K-SVD algorithm for designing dictionary with sparse representation, and it is proven to be … WebJan 17, 2024 · In this paper, we propose a novel dictionary learning with structured noise (DLSN) method which aims at handling noise in data from another perspective. As …
WebABSTRACT Most traditional seismic denoising algorithms will cause damage to useful signals, which are visible from the removed noise profiles and are known as signal … WebMar 2, 2024 · Non-parametric Bayesian Dictionary Learning with Beta process model in is proposed for removing Gaussian noise, the denoising performance of which is better …
WebAug 12, 2024 · The noise suppression method based on dictionary learning has shown great potential in magnetotelluric (MT) data processing. However, the constraints used in the existing algorithm’s method need to set manually, which significantly limits its application.
WebDictionary learning based on dip patch selection training for random noise attenuation CAS-3 JCR-Q2 SCIE EI Shaohuan Zu Hui Zhou Ru-Shan Wu Maocai Jiang Yangkang Chen. Geophysics May 2024. 阅读. 收藏. 分享. 引用. 摘要. ABSTRACTIn recent years, sparse representation is seeing increasing application to fundamental signal and image ... chinese refugees texas borderWebIn this paper, we propose a novel dictionary learning with structured noise (DLSN) method for handling noisy data. We decompose the original data into three parts: clean data, structured noise, and Gaussian noise, and then characterize them separately. We utilize the low-rank technique to preserve the inherent subspace structure of clean data. chinese regulator home equity loanWebABSTRACT Most traditional seismic denoising algorithms will cause damage to useful signals, which are visible from the removed noise profiles and are known as signal leakage. The local signal-and-noise orthogonalization method is an effective method for retrieving the leaked signals from the removed noise. Retrieving leaked signals while rejecting noise … chinese regime historyWebDec 29, 2024 · Dictionary learning, Noise denoising, Threshold. Introduction. With the rapid medical development, medical images are more and more important in medical engineering [1-3]. When sharing of information such as image information and position information [4-6], devices are inevitable to introduce noises to medical images. It is … chinese refuse to pay mortgagesWebIn this paper, we propose a novel dictionary learning with structured noise (DLSN) method which aims at handling noise in data from another perspective. As shown … grand staff braceWebApr 28, 2024 · Dictionary learning methods adaptively train their bases from the given data in an iterative manner; hence, they can capture more detailed features and achieve sparser representation than a method that uses a fixed basis. However, there also exists a good chance of erratic noise corrupting the dictionary because of the insufficiency of the L1 … grand staff and notesWebAiming at reducing computed tomography (CT) scan radiation while ensuring CT image quality, a new low-dose CT super-resolution reconstruction method based on combining a random forest with coupled dictionary learning is proposed. The random forest classifier finds the optimal solution of the mapping relationship between low-dose CT (LDCT) … grandstaff attorneys san antonio tx