| 基于Tetrolet变换与PCNN的图像增强 |
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| 引用本文： | 杨新华,翟逸飞.基于Tetrolet变换与PCNN的图像增强[J].计算机工程与应用,2014(19):178-181,191. |
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| 作者姓名： | 杨新华 翟逸飞 |
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| 作者单位： | 1. 兰州理工大学 电气工程与信息工程学院，兰州 730050; 甘肃省工业过程先进控制重点实验室，兰州 730050
2. 兰州理工大学 电气工程与信息工程学院,兰州,730050 |
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| 摘 要： | 针对传统图像增强方法易损失边缘对比度以及抗噪性不强的缺点提出了一种基于Tetrolet变换与PCNN结合的图像增强方法。对待增强图像分别进行Tetrolet变换,得到不同尺度的高通和低通子带系数,并将分解后的高通子带系数进行软阈值处理;把经处理后的各尺度高通子带轮廓图像序列作为PCNN神经网络增强算子的外部输入,进而得到增强后的高通子带系数;通过Tetrolet反变换获得增强后的结果图像。数值实验结果表明,该增强算法不但能够有效抑制噪声,而且能够很好地增强图像边缘轮廓的清晰度。
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| 关 键 词： | Tetrolet变换 脉冲耦合神经网络(PCNN) 软阈值 图像增强 |
Image enhancement based on tetrolet transform and PCNN |
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| YANG Xinhua,ZHAI Yifei.Image enhancement based on tetrolet transform and PCNN[J].Computer Engineering and Applications,2014(19):178-181,191. |
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| Authors: | YANG Xinhua ZHAI Yifei |
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| Affiliation: | YANG Xinhua,ZHAI Yifei(1.College of Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China; 2.Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou 730050, China) |
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| Abstract: | In order to solve the problem that the traditional image enhancement method is easy to damage the edge contrast and the shortcoming of noise resistance is not strong, this paper proposes an image enhancement method based on Tetrolet transform combined with PCNN. The different scales of high pass and low pass sub-bands are obtained by Tetrolet transform. Then the soft threshold processing of the decomposition image high-pass sub-bands coefficients is conducted. Finally,the reconstruct image is obtained by the inverse Tetrolet transformation. The experimental results show that this enhancement algorithm not only can suppress noise effectively, but also can enhance the sharpness of the image edge contour. |
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| Keywords: | Tetrolet transform Pulse Coupled Neural Network(PCNN) soft threshold image enhancement |
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