標題: AN EFFICIENT BAYESIAN FRAMEWORK FOR IMAGE ENHANCEMENT WITH SPATIAL CONSIDERATION
作者: Jen, Tzu-Cheng
Wang, Sheng-Jyh
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
關鍵字: Image Enhancement;MAP estimation
公開日期: 2010
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.
URI: http://hdl.handle.net/11536/26188
http://dx.doi.org/10.1109/ICIP.2010.5650002
ISBN: 978-1-4244-7994-8
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5650002
期刊: 2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING
起始頁: 3285
結束頁: 3288
Appears in Collections:Conferences Paper


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