液晶与显示, 2014, 29 (2): 275, 网络出版: 2014-04-09   

基于LoG算子改进的自适应阈值小波去噪算法

Improved self-adaptive threshold wavelet denoising analysis based on LoG operator
作者单位
福州大学 物理与信息工程学院, 福建 福州 350002
摘要
图像在传输过程中会受到各种噪声干扰, 为了实现消除噪声的目的, 提出一种基于LoG算子改进的自适应阈值去噪算法。首先, 利用LoG算子提取图像的边缘特征信息。接着, 根据图像的边缘特征和非边缘特征分别求取改进的阈值函数: 对于图像非边缘部分的阈值函数, 在软阈值函数的基础上添加一个阈值修正系数, 构建新的阈值函数; 对于图像边缘部分的阈值函数, 将边缘部分小波系数附近的能量和阈值相结合, 构建新的阈值函数。最后利用改进的阈值函数对图像R、G、B 3个通道分别处理, 保留图像所有的细节信息。实验结果表明,消噪后图像与含噪图像的PSNR值高于传统自适应算法1209%; MAE值低于传统自适应算法22%。该算法有效保存了图像的边缘信息, 综合去噪效果明显提高。
Abstract
The image will be affected by various noise interference in the process.In order to eliminate the noise of the image, an improved self-adaptive threshold wavelet denoising analysis based on LoG operator was proposed.First, the image edge character information was extracted by LoG operator.Then,according to the edge of the image features and the no-edge of the image features, the improved threshold function was calculated respectively: on the basis of soft-thresholding function,a modified threshold coefficient was added for the threshold function in the image no-edge areas; in the no-edge areas, a new threshold function was built combining the energy near the wavelet coefficients with threshold. Finally,dealing with the red,green and blue(R,G,B) channels separately by the improved threshold function, all the details of the image were reserved.Experimental results show that PSNR of the image was above 1209% compared with the traditional adaptive algorithm; MAE of the image was below 22% compared with the traditional adaptive algorithm.The image of this algorithm has a better quality than others,keeping the edge’s information effectively, the integrative denoising is improved obviously.

董雪, 林志贤, 郭太良. 基于LoG算子改进的自适应阈值小波去噪算法[J]. 液晶与显示, 2014, 29(2): 275. DONG Xue, LIN Zhi-xian, GUO Tai-liang. Improved self-adaptive threshold wavelet denoising analysis based on LoG operator[J]. Chinese Journal of Liquid Crystals and Displays, 2014, 29(2): 275.

本文已被 6 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!