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改进双边滤波和阈值函数的图像增强算法
引用本文:常戬,贺春泽,董育理,任营.改进双边滤波和阈值函数的图像增强算法[J].计算机工程与应用,2020,56(3):207-213.
作者姓名:常戬  贺春泽  董育理  任营
作者单位:辽宁工程技术大学 软件学院,辽宁 葫芦岛 125105
摘    要:针对基于单尺度Retinex算法产生的图像泛灰现象和光晕现象、基于双边滤波Retinex算法的泛灰现象及噪声放大现象。提出基于小波变换的改进双边滤波的Retinex图像增强算法和改进阈值函数去噪算法。该方法对图像进行小波分解,获得图像的低频和高频系数;采用改进双边滤波的Retinex算法对图像低频系数进行处理,采用改进阈值函数对高频系数进行处理;采用离散小波反变换得到增强后的重构图像;对重构图像进行分段性线性变换,增强图像对比度。实验结果表明,该方法避免了图像泛灰和光晕现象,并有效去除了噪声,细节丰富,对比度强,为图像后续处理奠定基础。

关 键 词:小波分解  改进双边滤波  Retinex算法  改进阈值函数  离散小波反变换  分段性线性变换  

Improved Image Enhancement Algorithm for Bilateral Filtering and Threshold Function
CHANG Jian,HE Chunze,DONG Yuli,REN Ying.Improved Image Enhancement Algorithm for Bilateral Filtering and Threshold Function[J].Computer Engineering and Applications,2020,56(3):207-213.
Authors:CHANG Jian  HE Chunze  DONG Yuli  REN Ying
Affiliation:School of Software, Liaoning Technical Universty, Huludao, Liaoning 125105, China
Abstract:Aiming at the image gray phenomenon and halo phenomenon based on single-scale Retinex algorithm,gray phenomenon based on bilateral filtering Retinex algorithm and noise amplification phenomenon.An improved two-sided filtering based on wavelet transform and a modified threshold function denoising algorithm are proposed.The image is decomposed by wavelet transform to obtain the low-frequency and high-frequency coefficients of the image.The low-frequency coefficients of the image are processed by improved bilateral filtering Retinex algorithm,and the high-frequency coefficients are processed by improved threshold function.The enhanced reconstructed image is obtained by inverse discrete wavelet transform.The reconstructed image is reconstructed like segmented linear transformation,enhance image contrast.The experimental results show that this method avoids the phenomenon of image gray and halo,and effectively removes noise,rich details and strong contrast,which lays the foundation for image follow-up processing.
Keywords:wavelet decomposition  improved bilateral filtering  Retinex algorithm  improved threshold function  dis crete wavelet inverse transform  piecewise linear transform
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