Denoising of hyperspectral imagery using a spatial-spectral domain mixing prior

CASIA OpenIR > 智能制造技术与系统研究中心 > 多维数据分析（彭思龙）-技术团队

	Denoising of hyperspectral imagery using a spatial-spectral domain mixing prior
	Chen Shaolin; Hu Xiyuan; Peng Silong
	2012
会议名称	2012 20th International Conference on Geoinformatics Geoinformatics 2012
会议日期	2012/6/15-2012/6/17
会议地点	中国香港Hong Kong China
摘要	By 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.
关键词	Hyperspectral Images Image Denoising Maimum a Posterior (Map) Spectral Continuit Miing Priorposterior (Map) Spectral Continuit Miing Prior
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12874
专题	智能制造技术与系统研究中心_多维数据分析（彭思龙）-技术团队
通讯作者	Peng Silong
推荐引用方式 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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文件名称/大小	文献类型	版本类型	开放类型	使用许可
Denoising of hypersp（2609KB）	会议论文		暂不开放	CC BY-NC-SA