Hyperspectral Image Restoration under Complex Multi-Band Noises
Hyperspectral Image Restoration under Complex Multi-Band Noises
复制标题
复杂多波段噪声下的高光谱图像恢复
DOI：
10.3390/rs10101631
复制
发表时间：
2018-10
期刊：
影响因子：
5
通讯作者：
Qian Zhao
中科院分区：
文献类型：
--
作者：
Zongsheng Yue;Deyu Meng;Yongqing Sun;Qian Zhao
高光谱图像在获取过程中经常受到高斯噪声、脉冲噪声、条纹噪声、截止时间等多种噪声的干扰，实际高光谱图像的不同波段通常包含不同类型和程度的噪声。而目前的HSI恢复方法很少考虑这样的频带噪声的独特性问题，本研究精心构建了一个新的HSI恢复技术，旨在更忠实和全面地考虑到这样的噪声特性。特别地，通过两级分层狄利克雷过程（HDP）来建模HSI噪声结构，每个频带的噪声由狄利克雷过程高斯混合模型（DP-GMM）来描述，其中其复杂度可以以自动方式灵活地适应。此外，每个频带的DP-GMM来自于更高级别的DP-GMM，该DP-GMM将不同频带的噪声联系起来。设计了求解该模型的变分贝叶斯算法，推导出了所有参数的封闭形式更新方程。实验结果表明，该方法在平均峰值信噪比（MPSNR）方面比现有方法平均高1 dB，在平均结构相似性指数（MSSIM）和相对误差综合维数（ERGAS）方面表现更好.
Hyperspectral images (HSIs) are always corrupted by complicated forms of noise during the acquisition process, such as Gaussian noise, impulse noise, stripes, deadlines and so on. Specifically, different bands of the practical HSIs generally contain different noises of evidently distinct type and extent. While current HSI restoration methods give less consideration to such band-noise-distinctness issues, this study elaborately constructs a new HSI restoration technique, aimed at more faithfully and comprehensively taking such noise characteristics into account. Particularly, through a two-level hierarchical Dirichlet process (HDP) to model the HSI noise structure, the noise of each band is depicted by a Dirichlet process Gaussian mixture model (DP-GMM), in which its complexity can be flexibly adapted in an automatic manner. Besides, the DP-GMM of each band comes from a higher level DP-GMM that relates the noise of different bands. The variational Bayes algorithm is also designed to solve this model, and closed-form updating equations for all involved parameters are deduced. The experiment indicates that, in terms of the mean peak signal-to-noise ratio (MPSNR), the proposed method is on average 1 dB higher compared with the existing state-of-the-art methods, as well as performing better in terms of the mean structural similarity index (MSSIM) and Erreur Relative Globale Adimensionnelle de Synthèse (ERGAS).
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影响因子：
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