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基于PCNN与LR的低对比度图像增强方法

Method of low contrast image enhancement based on PCNN and LR
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摘要 图像增强是指对图像进行加工,以获得更"好"的视觉效果的一种图像处理技术。由于图像的最终接收者是人,所以评价图像"好坏"的关键在于其是否符合人类视觉系统的特性。针对低对比度图像,结合人眼视觉神经系统的感知特性,提出了一种基于PCNN与LR模型的图像增强方法。分析和仿真结果表明,该法能够较好地突出图像的边缘细节信息,明显地改善图像的视觉效果。 Image enhancement is an algorithm which is performed on image, to make it seemed ＂better＂.Since human being is the final receiver of the image,the key point of the image assessment is that it should be in conformity with the characteristics of human visual system.In this paper,a new method of low contrast image enhancement is presented based on PCNN and LR models in conjunction with characteristics of human visual consciousness.Results of analysis and experiments show that this method strengthens the details of edges and ameliorates visual effect obviously.
作者 朱昊 金文标
机构地区 重庆邮电大学计算机科学与技术学院
出处 《计算机工程与应用》 CSCD 北大核心 2008年第17期162-165,共4页 Computer Engineering and Applications
关键词 脉冲耦合神经网络 人眼视觉特性 图像增强 对比度 Pulse Coupled Neural Networks（PCNN） Human Visual System （HVS） image enhancement image contrast
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献16

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共引文献31

计算机工程与应用
2008年 第17期

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