An efficient Bayesian framework for image enhancement with spatial consideration

Tzu Cheng Jen*, Sheng-Jyh Wang

*Corresponding author for this work

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

In this paper, a Bayesian framework is proposed for image enhancement. We model the image enhancement problem as a maximum a posteriori (MAP) estimation problem and the posteriori distribution function is formulated based on the local structures and local gradients of the given image. By solving the MAP estimation problem, image contrast gets properly enhanced while image noise gets suppressed at the same time. Moreover, since directly solving an MAP estimation problem is impractical for real-time applications, we further simplify the process to generate an intensity mapping function that achieves comparable performance in image enhancement. Simulation results have demonstrated the applicability of the proposed method in providing a flexible and efficient way for image enhancement.

原文English
主出版物標題2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
頁面3285-3288
頁數4
DOIs
出版狀態Published - 1 十二月 2010
事件2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
持續時間: 26 九月 201029 九月 2010

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
ISSN(列印)1522-4880

Conference

Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
國家Hong Kong
城市Hong Kong
期間26/09/1029/09/10

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