成像系统中的逆问题及一般贝叶斯反演框架
Inverse problems in imaging systems and the general Bayesian inversion frawework
摘要：
在本文中，首先提出了大量的反问题，出现在仪器，在计算机成像系统和计算机视觉。然后给出了它们的通用正演模型，并提出了相应的反演问题。然后，经典的分析和最小二乘方法，这些不适定的反问题的不足之处，贝叶斯估计框架，可以处理，在一个连贯的方式，所有这些问题。在贝叶斯反演框架中，主要步骤之一是未知量的先验建模。为此，提出了大量的这种模型，特别是复合隐马尔可夫模型。然后，简要介绍了贝叶斯估计的主要计算工具。最后，对一些特殊情况进行了详细的研究，并给出了新的结果。
英文摘要：
In this paper, first a great number of inverse problems which arise in instrumentation, in computer imaging systems and in computer vision are presented. Then a common general forward modeling for them is given and the corresponding inversion problem is presented. Then, after showing the inadequacy of the classical analytical and least square methods for these ill posed inverse problems, a Bayesian estimation framework is presented which can handle, in a coherent way, all these problems. One of the main steps, in Bayesian inversion framework is the prior modeling of the unknowns. For this reason, a great number of such models and in particular the compound hidden Markov models are presented. Then, the main computational tools of the Bayesian estimation are briefly presented. Finally, some particular cases are studied in detail and new results are presented.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
