SIAM Journal on Imaging Sciences最新文献_第7页

An Operator Theory for Analyzing the Resolution of Multi-illumination Imaging Modalities 多照度成像模式分辨率分析的算子理论

IF 2.1 3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-11-15 DOI: 10.1137/23m1551730

Ping Liu, Habib Ammari

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引用次数: 1

Spherical Framelets from Spherical Designs 来自球形设计的球形框架

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-11-14 DOI: 10.1137/22m1542362

Yuchen Xiao, Xiaosheng Zhuang

引用次数: 2

The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution 对分离式吉布斯采样器的再考察:改进其算法结构和增强目标分布

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-11-10 DOI: 10.1137/22m1506122

Marcelo Pereyra, Luis A. Vargas-Mieles, Konstantinos C. Zygalakis

{"title":"The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution","authors":"Marcelo Pereyra, Luis A. Vargas-Mieles, Konstantinos C. Zygalakis","doi":"10.1137/22m1506122","DOIUrl":"https://doi.org/10.1137/22m1506122","url":null,"abstract":"Developing efficient Bayesian computation algorithms for imaging inverse problems is challenging due to the dimensionality involved and because Bayesian imaging models are often not smooth. Current state-of-the-art methods often address these difficulties by replacing the posterior density with a smooth approximation that is amenable to efficient exploration by using Langevin Markov chain Monte Carlo (MCMC) methods. An alternative approach is based on data augmentation and relaxation, where auxiliary variables are introduced in order to construct an approximate augmented posterior distribution that is amenable to efficient exploration by Gibbs sampling. This paper proposes a new accelerated proximal MCMC method called latent space SK-ROCK (ls SK-ROCK), which tightly combines the benefits of the two aforementioned strategies. Additionally, instead of viewing the augmented posterior distribution as an approximation of the original model, we propose to consider it as a generalisation of this model. Following on from this, we empirically show that there is a range of values for the relaxation parameter for which the accuracy of the model improves, and propose a stochastic optimisation algorithm to automatically identify the optimal amount of relaxation for a given problem. In this regime, ls SK-ROCK converges faster than competing approaches from the state of the art, and also achieves better accuracy since the underlying augmented Bayesian model has a higher Bayesian evidence. The proposed methodology is demonstrated with a range of numerical experiments related to image deblurring and inpainting, as well as with comparisons with alternative approaches from the state of the art. An open-source implementation of the proposed MCMC methods is available from https://github.com/luisvargasmieles/ls-MCMC.","PeriodicalId":49528,"journal":{"name":"SIAM Journal on Imaging Sciences","volume":" 409","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135185986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Sequential Model Correction for Nonlinear Inverse Problems 非线性逆问题的序贯模型校正

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-19 DOI: 10.1137/23m1549286

Arttu Arjas, Mikko J. Sillanpää, Andreas S. Hauptmann

引用次数: 0

A Common Lines Approach for Ab Initio Modeling of Molecules with Tetrahedral and Octahedral Symmetry 四面体和八面体对称分子从头建模的公共线方法

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-18 DOI: 10.1137/22m150383x

Adi Shasha Geva, Yoel Shkolnisky

引用次数: 1

Convolutional Forward Models for X-Ray Computed Tomography x射线计算机断层扫描的卷积正演模型

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-12 DOI: 10.1137/21m1464191

Kai Zhang, Alireza Entezari

引用次数: 0

A Data-Assisted Two-Stage Method for the Inverse Random Source Problem 逆随机源问题的数据辅助两阶段法

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-12 DOI: 10.1137/23m1562561

Peijun Li, Ying Liang, Yuliang Wang

引用次数: 0

(boldsymbol{L_1-beta L_q}) Minimization for Signal and Image Recovery (boldsymbol{L_1-beta L_q}) 最小化的信号和图像恢复

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-11 DOI: 10.1137/22m1525363

Limei Huo, Wengu Chen, Huanmin Ge, Michael K. Ng

引用次数: 0

Subaperture-Based Digital Aberration Correction for Optical Coherence Tomography: A Novel Mathematical Approach 基于子孔径的光学相干层析成像数字像差校正:一种新的数学方法

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-11 DOI: 10.1137/22m1543240

Simon Hubmer, Ekaterina Sherina, Ronny Ramlau, Michael Pircher, Rainer Leitgeb

引用次数: 0

Short Communication: Localized Adversarial Artifacts for Compressed Sensing MRI 短通信:压缩感知MRI的局部对抗伪影

3区数学

SIAM Journal on Imaging Sciences Pub Date : 2023-10-10 DOI: 10.1137/22m1503221

Rima Alaifari, Giovanni S. Alberti, Tandri Gauksson

引用次数: 0