泊松损坏数据的复杂性正则化去噪

Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101) Pub Date : 2000-09-10 DOI:10.1109/ICIP.2000.899343

Juan Liu, P. Moulin

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引用次数: 5

摘要

将复杂正则化原理应用于泊松成像。我们在图像空间中提出了一种自然失真测度，并提出了复杂度正则化估计与率失真理论之间的联系。为了计算的可追溯性，我们采用约束编码如JPEG或SPIHT来近似解决优化问题。此外，我们还设计了一个简单的预测编码器，它可以很好地解决我们的优化问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Complexity-regularized denoising of Poisson-corrupted data

We apply the complexity-regularization principle to Poisson imaging. We formulate a natural distortion measure in the image space, and present a connection between complexity-regularized estimation and rate-distortion theory. For computational tractability, we apply constrained coders such as JPEG or SPIHT to solve the optimization problem approximately. Also, we design a simple predictive coder which lends itself well to our optimization problem.

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Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101)

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