CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
Denoising of hyperspectral imagery using a spatial-spectral domain mixing prior
Chen Shaolin; Hu Xiyuan; Peng Silong
2012
Conference Name2012 20th International Conference on Geoinformatics Geoinformatics 2012
Conference Date2012/6/15-2012/6/17
Conference Place中国香港Hong Kong China
AbstractBy introducing a novel spatial-spectral domain mixing prior this paper establishes a maimum a posterior (MAP) framework for hyperspectral images (HSls) denoising. The proposed mixing prior takes advantage of different properties of HSI in the spatial and spectral domain. Furthermore we proposed a spatially adaptive weighted prior combining smoothing prior and discontinuity-preserving prior in the spectral domain. The weights can be defned as a function of the spectral discontinuity measure (DM). For minimizing the objective function a half-quadratic optimization algorithm is used. The experimental results illustrate that our proposed model can get a higher signal-to-noise ratio (SNR) than using only smoothing prior or discontinuity-preserving prior.
KeywordHyperspectral Images Image Denoising Maimum a Posterior (Map) Spectral Continuit Miing Priorposterior (Map) Spectral Continuit Miing Prior
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12874
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorPeng Silong
Recommended Citation
GB/T 7714
Chen Shaolin,Hu Xiyuan,Peng Silong. Denoising of hyperspectral imagery using a spatial-spectral domain mixing prior[C],2012.
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