福州大学学报（自然科学版）2018，Vol.46Issue(1)：45-51,7.DOI:10.7631/issn.1000-2243.16246
基于变分贝叶斯推理的高光谱图像恢复
Hyperspectral image restoration based on variational Bayesian inference
摘要
Abstract
We propose a methed for hyperspectral image restoration based on variational Bayesian methed.One hand,we propose a likelihood function term accounting for Gaussian noise,the other hand,we propose the prior distribution for the sparsity of image in the transformation domain based on the wavelet base.Then we give the maximization posterior model of the image to be estimated and the relevant super-parameter.At last,we infer the maximization posterior function based on variational Bayesian method.From the experiments on the real hyperspectral images,the results show the proposed method can surpass the well known methods,both in terms of indexes and visual effect.关键词
高光谱图像/稀疏表示/超参数/变分贝叶斯Key words
hyperspectral image/sparse representation/super-parameter/variational Bayesian分类
信息技术与安全科学引用本文复制引用
邹长忠..基于变分贝叶斯推理的高光谱图像恢复[J].福州大学学报（自然科学版）,2018,46(1):45-51,7.基金项目
国家自然科学基金资助项目(61473330) （61473330）
福建省教育厅基金资助项目(JK2017003) （JK2017003）
