Depth restoration from defocused images using simulated annealing

K. Prasad, R. Mammone
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引用次数: 3

Abstract

The recovery of depth from defocused images is formulated as a 3-D image restoration problem. A defocused image is modeled as the combinatorial outcome of the depths and intensities of the volume elements (voxels) of an opaque 3-D object. A large depth-of-field image is used to constrain the intensities of the voxels. The depths of voxels are estimated from a highly defocused image by using simulated annealing to solve a constrained optimization problem. It is concluded that the method provides a framework for high-resolution depth recovery from defocused images. The method is computationally-intensive; however, it is amenable to parallel processing and is well suited for small field-of-interest applications.<>
利用模拟退火技术对散焦图像进行深度恢复
从离焦图像中恢复深度被表述为三维图像恢复问题。散焦图像被建模为不透明三维物体的体素(体素)的深度和强度的组合结果。使用大景深图像来约束体素的强度。利用模拟退火算法对高度散焦图像进行体素深度估计,解决了约束优化问题。该方法为离焦图像的高分辨率深度恢复提供了一个框架。该方法计算量大;然而,它可以并行处理,非常适合小型领域的应用。
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