基于层次贝叶斯建模的遥感图像去噪方法
Science of Surveying and Mapping（2014）
Abstract
场景信息建模是图像理解的高层认知部分.本文基于压缩感知理论和图像理解的思想,用非参数贝叶斯字典学习方法对遥感图像进行去噪处理;对图像场景的空间结构建立层次贝叶斯概率模型,利用Gibbs抽样进行贝叶斯推理.通过学习获得包含图像空间结构信息的字典,并用于图像的重建去噪,使去噪图像的峰值信噪比(PSNR)值提高了40％以上.
MoreKey words
compressive sensing,image understanding,hierarchical Bayesian model,dictionary learning,de-noising
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