BAYESIAN IMAGE-RESTORATION, WITH 2 APPLICATIONS IN SPATIAL STATISTICS
BAYESIAN IMAGE-RESTORATION, WITH 2 APPLICATIONS IN SPATIAL STATISTICS
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DOI：
10.1007/bf00116466
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发表时间：
1991-03-01
影响因子：
1
通讯作者：
MOLLIE, A
中科院分区：
文献类型：
--
作者：
BESAG, J;YORK, J;MOLLIE, A
贝叶斯图像分析最近引起了人们的极大兴趣，包括模糊和噪声的去除、对象边界的检测、纹理的分类以及从噪声较低的维视图重建二维或三维场景。也许最直接的任务是图像恢复，尽管人们经常认为这是一个相对次要的实际重要性领域。本文提出了相反的观点，因为空间数据分析中的许多问题可以解释为图像恢复问题。此外，所涉及的数据量允许常规使用计算机密集型方法，如吉布斯采样器，这对传统图像来说还不可行。文中给出了两个例子，一个是考古学，另一个是流行病学。在此之前，对基于像素的贝叶斯图像分析进行了部分回顾。
There has been much recent interest in Bayesian image analysis, including such topics as removal of blur and noise, detection of object boundaries, classification of textures, and reconstruction of two- or three-dimensional scenes from noisy lower-dimensional views. Perhaps the most straightforward task is that of image restoration, though it is often suggested that this is an area of relatively minor practical importance. The present paper argues the contrary, since many problems in the analysis of spatial data can be interpreted as problems of image restoration. Furthermore, the amounts of data involved allow routine use of computer intensive methods, such as the Gibbs sampler, that are not yet practicable for conventional images. Two examples are given, one in archeology, the other in epidemiology. These are preceded by a partial review of pixel-based Bayesian image analysis.