Simultaneous depth recovery and image restoration from defocused images

A. Rajagopalan, S. Chaudhuri
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引用次数: 15

Abstract

We propose a method for simultaneous recovery of depth and restoration of scene intensity, given two defocused images of a scene. The space-variant blur parameter and the focused image of the scene are modeled as Markov random fields (MRFs). Line fields are included to preserve discontinuities. The joint posterior distribution of the blur parameter and the intensity process is examined for locality property and we derive an important result that the posterior is again Markov. The result enables us to obtain the maximum a posterior (MAP) estimates of the blur parameter and the focused image, within reasonable computational limits. The estimates of depth and the quality of the restored image are found to be quite good, even in the presence of discontinuities.
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同时深度恢复和图像恢复从散焦图像
我们提出了一种同时恢复景深和恢复场景强度的方法,给出了一个场景的两个散焦图像。将空间变模糊参数和场景聚焦图像建模为马尔可夫随机场(mrf)。包括线场以保持不连续。研究了模糊参数和强度过程的联合后验分布的局部性,得到了后验仍然是马尔可夫的重要结果。结果使我们能够在合理的计算范围内获得模糊参数和聚焦图像的最大后验(MAP)估计。我们发现,即使在存在不连续的情况下,对深度的估计和恢复图像的质量也相当好。
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