Nonuniform sampling, image recovery from sparse data and the discrete sampling theorem.
Nonuniform sampling, image recovery from sparse data and the discrete sampling theorem.
复制标题
非均匀采样、稀疏数据图像恢复和离散采样定理。
DOI：
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发表时间：
2008
影响因子：
1.9
通讯作者：
B. Fishbain
中科院分区：
文献类型：
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作者：
L. Yaroslavsky;G. Shabat;B. G. Salomon;I. Ideses;B. Fishbain
在许多应用中，采样数据以不规则的方式收集，或者部分丢失或不可用。在这些情况下，有必要将不规则采样的信号转换为规则采样的信号或恢复丢失的数据。我们解决这个问题的框架中的离散采样定理的带限离散信号，具有有限数量的非零变换系数在一定的变换域。从稀疏样本的图像唯一恢复的条件，制定，然后分析各种变换。应用程序演示的例子图像超分辨率和图像重建稀疏投影。
In many applications, sampled data are collected in irregular fashion or are partly lost or unavailable. In these cases, it is necessary to convert irregularly sampled signals to regularly sampled ones or to restore missing data. We address this problem in the framework of a discrete sampling theorem for band-limited discrete signals that have a limited number of nonzero transform coefficients in a certain transform domain. Conditions for the image unique recovery, from sparse samples, are formulated and then analyzed for various transforms. Applications are demonstrated on examples of image superresolution and image reconstruction from sparse projections.