Image restoration based on total variation has been widely studied owing to its edgepreservation properties.In this study,we consider the total variation infimal convolution(TV-IC)image restoration model for eliminati...Image restoration based on total variation has been widely studied owing to its edgepreservation properties.In this study,we consider the total variation infimal convolution(TV-IC)image restoration model for eliminating mixed Poisson-Gaussian noise.Based on the alternating direction method of multipliers(ADMM),we propose a complete splitting proximal bilinear constraint ADMM algorithm to solve the TV-IC model.We prove the convergence of the proposed algorithm under mild conditions.In contrast with other algorithms used for solving the TV-IC model,the proposed algorithm does not involve any inner iterations,and each subproblem has a closed-form solution.Finally,numerical experimental results demonstrate the efficiency and effectiveness of the proposed algorithm.展开更多
Poisson-Gaussian noise is the basis of image formation for a great number of imaging systems used in variety of applications, including medical and astronomical imaging. In wavelet domain, the application of Bayesian ...Poisson-Gaussian noise is the basis of image formation for a great number of imaging systems used in variety of applications, including medical and astronomical imaging. In wavelet domain, the application of Bayesian estimation method with generalized Anscombe transform in Poisson-Gaussian noise reduction algorithm has shown remark- able success over the last decade. The generalized Anscombe transform is exerted to convert the Poisson-Gaussian noise into an additive white Gaussian noise （AWGN）. So, the resulting data can be denoised with any algorithm designed for the removal of AWGN. Here, we present simple form of minimum mean square error （MMSE） estimator for logistic distribution in Poisson-Gaussian noise. The experimental results show that the proposed method yields good denoising results.展开更多
为了准确预测与深层页岩气藏压裂改造相关的两项重要指标——杨氏模量和泊松比,基于三轴抗压强度实验结果,采用高斯过程回归(Gaussian Process Regression,GPR)方法,建立了四川盆地东南部林滩场地区奥陶系上统五峰组—志留系下统龙马溪...为了准确预测与深层页岩气藏压裂改造相关的两项重要指标——杨氏模量和泊松比,基于三轴抗压强度实验结果,采用高斯过程回归(Gaussian Process Regression,GPR)方法,建立了四川盆地东南部林滩场地区奥陶系上统五峰组—志留系下统龙马溪组一段(以下简称龙一段)深层页岩气储层的岩石力学参数预测模型,并对计算得到的杨氏模量和泊松比进行了定量评价。研究结果表明:①该区深层页岩储层样品受内部应力薄弱面的影响,随温度和压力的升高,应力—应变曲线在峰后阶段的波动特征更为明显;②GPR模型可以降低页岩储层“纵向异性、横观同性”的影响,残差分布均表现为近似对称的等腰三角形特征,训练时间较短、预测速度较快,岩石力学参数(杨氏模量和泊松比)的预测准确率和GPR模型的置信度均超过90%,预测精度得以显著提高;③单井岩石力学参数(杨氏模量和泊松比)预测曲线与岩石力学实验结果具有较好的拟合效果,可以真实地反映该区五峰组—龙一段深层页岩储层的岩石力学性质。结论认为,五峰组—龙一段储层的③号层底部和②号层具有较强的脆性特征和良好的工程改造条件,是该区深层页岩气后续开发的主力层段。展开更多
基金supported by the National Natural Science Foundations of China(Grant Nos.12061045,12031003)by the Guangzhou Education Scientific Research Project 2024(Grant No.202315829)+1 种基金by the Guangzhou University Research Projects(Grant No.RC2023061)by the Jiangxi Provincial Natural Science Foundation(Grant No.20224ACB211004).
文摘Image restoration based on total variation has been widely studied owing to its edgepreservation properties.In this study,we consider the total variation infimal convolution(TV-IC)image restoration model for eliminating mixed Poisson-Gaussian noise.Based on the alternating direction method of multipliers(ADMM),we propose a complete splitting proximal bilinear constraint ADMM algorithm to solve the TV-IC model.We prove the convergence of the proposed algorithm under mild conditions.In contrast with other algorithms used for solving the TV-IC model,the proposed algorithm does not involve any inner iterations,and each subproblem has a closed-form solution.Finally,numerical experimental results demonstrate the efficiency and effectiveness of the proposed algorithm.
文摘Poisson-Gaussian noise is the basis of image formation for a great number of imaging systems used in variety of applications, including medical and astronomical imaging. In wavelet domain, the application of Bayesian estimation method with generalized Anscombe transform in Poisson-Gaussian noise reduction algorithm has shown remark- able success over the last decade. The generalized Anscombe transform is exerted to convert the Poisson-Gaussian noise into an additive white Gaussian noise （AWGN）. So, the resulting data can be denoised with any algorithm designed for the removal of AWGN. Here, we present simple form of minimum mean square error （MMSE） estimator for logistic distribution in Poisson-Gaussian noise. The experimental results show that the proposed method yields good denoising results.
文摘为了准确预测与深层页岩气藏压裂改造相关的两项重要指标——杨氏模量和泊松比,基于三轴抗压强度实验结果,采用高斯过程回归(Gaussian Process Regression,GPR)方法,建立了四川盆地东南部林滩场地区奥陶系上统五峰组—志留系下统龙马溪组一段(以下简称龙一段)深层页岩气储层的岩石力学参数预测模型,并对计算得到的杨氏模量和泊松比进行了定量评价。研究结果表明:①该区深层页岩储层样品受内部应力薄弱面的影响,随温度和压力的升高,应力—应变曲线在峰后阶段的波动特征更为明显;②GPR模型可以降低页岩储层“纵向异性、横观同性”的影响,残差分布均表现为近似对称的等腰三角形特征,训练时间较短、预测速度较快,岩石力学参数(杨氏模量和泊松比)的预测准确率和GPR模型的置信度均超过90%,预测精度得以显著提高;③单井岩石力学参数(杨氏模量和泊松比)预测曲线与岩石力学实验结果具有较好的拟合效果,可以真实地反映该区五峰组—龙一段深层页岩储层的岩石力学性质。结论认为,五峰组—龙一段储层的③号层底部和②号层具有较强的脆性特征和良好的工程改造条件,是该区深层页岩气后续开发的主力层段。
