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基于可调Q因子小波变换的芯片图像去噪研究 被引量:1

Research on Chip Image Denoising Based on Tunable Q-factor Wavelet Transform
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摘要 噪声会降低芯片图像的字符识别准确率,为了去除芯片图像的噪声干扰,并保留芯片图像的字符细节,提出了基于参数优化的可调Q因子小波变换(TQWT)的芯片图像去噪方法。首先根据图片的弱纹理区域,使用极大似然估计来估计噪声强度,进而优化TQWT的参数。然后,根据最优参数,使用TQWT对含噪图像沿水平和竖直方向分解,剔除高频噪声子带,使用剩余子带进行重构去噪。实验表明,优化参数后的TQWT能将噪声完全分离,可以在去噪的同时保留字符的细节信息,在视觉效果、峰值信噪比和结构相似性上都优于对比算法。 Noise can reduce the character recognition accuracy of chip image,in order to remove the noise of chip image and retain the character details of the chip image,a chip image denoising method based on parameter optimization tunable Q-factor wavelet transform(TQWT)was proposed.First,according to the weak texture area of the picture,maximum likelihood estimation was used to estimate the noise intensity,and then the parameters of TQWT were optimized.Then,according to the optimal parame⁃ters,TQWT was used to decompose the noisy image in the horizontal and vertical directions,and remove high⁃frequency noise sub⁃bands,and the remaining sub⁃bands for reconstruction was used to denoise.Experiments show that TQWT with optimized parame⁃ters can completely separate the noise and retain the detailed information of the characters while denoising.It is better than the comparison algorithm in terms of visual effects,peak signal⁃to⁃noise ratio and structural similarity.
作者 樊博 田瑞 金旭荣 郭林明 FAN Bo;TIAN Rui;JIN Xu-rong;GUO Lin-ming(State Grid Ningxia Marketing Service Center(Metrology Center),Yinchuan 750011,China;College of Electrical Engineering,Sichuan University,Chengdu 610065,China)
出处 《仪表技术与传感器》 CSCD 北大核心 2021年第12期106-110,共5页 Instrument Technique and Sensor
基金 国家电网有限公司科技项目(5229DK200006)。
关键词 可调Q因子小波变换 噪声估计 图像去噪 芯片图像 tunable Q-factor wavelet transform noise estimation image denoising chip image
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