Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (9): 205-207.

• 图形、图像、模式识别 • Previous Articles     Next Articles

Speckle denoising new method for reconstructed image of digital holography

JIA Qin1,2, LI Zhiquan1   

  1. 1.Institute of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
    2.Department of Information Engineering, Environmental Management College of China, Qinhuangdao, Hebei 066004, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2012-03-21 Published:2012-04-11

数字全息再现图像散斑噪声消除新方法

贾 勤1,2,李志全1   

  1. 1.燕山大学 电气工程学院,河北 秦皇岛 066004
    2.中国环境管理干部学院 信息工程系,河北 秦皇岛 066004

Abstract: In order to eliminate the speckle noise in the reconstructed image of digital holography, on the basis of retaining the image details as much as possible at the same time of reducing noise, a method of image edge keeping and speckle noise denoising based on wavelet transform is proposed. It analyzes the principle of wavelet modulus maxima used in image edge detection and wavelet threshold denoising based on Neyman-Pearson criterion. A kind of speckle noise reduction method in the reconstructed image of digital holography is given. It gets the edge image by the wavelet modulus maxima method, and then denoises the reconstructed image by wavelet threshold method based on Neyman-Pearson criterion. The final reconstructed image is obtained by merging the denoised image with the edge image. The result shows that the method can reduce the speckle noise and keep the edge of image well.

Key words: digital holography, speckle noise, wavelet transform, wavelet modulus maxima, Neyman-Pearson criterion

摘要: 为了消除数字全息再现像中存在的相干散斑噪声,在去除噪声并保留图像细节的基础上,提出了基于小波变换的边缘保持散斑噪声去噪方法;通过分析小波变换模极大值边缘检测和基于Neyman-Pearson准则的小波阈值去噪方法的原理,提出并应用了一种数字全息再现像散斑噪声去噪方法,利用小波模极大值方法获得边缘图像,通过基于Neyman-Pearson准则的小波阈值去噪,去噪后的图像与边缘图像合并后得到最终再现图像。研究结果表明,该方法能够较好地在去除散斑噪声的同时保留图像细节。

关键词: 数字全息, 相干散斑噪声, 小波变换, 模极大值, Neyman-Pearson准则