Reconstructed image enhancement of digital holography in contourlet domain based on particle swarm optimization

被引：0

作者：

Wu, Yiquan ^{[1
,2
]}

Yin, Jun ^{[1
]}

机构：

[1] College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing

[2] State Key Laboratory of Transient Optics and Photonics, Xi'an

来源：

Zhongguo Jiguang/Chinese Journal of Lasers | 2013年 / 40卷 / 08期

关键词：

Adaptive image enhancement; Contourlet transform; Gray-scale transform; Holography; Speckle noise; Uniform searching particle swarm optimization;

D O I：

10.3788/CJL201340.0809002

中图分类号：

学科分类号：

摘要：

Aiming at the problem of low contrast, blurred edges and textures, and speckle noise of reconstructed image in digital holography, an adaptive enhancement method for reconstructed image of digital holography in contourlet domain based on uniform searching particle swarm optimization is proposed. Median filtering algorithm is used to suppress speckle noise of the reconstructed image. After the contourlet decomposition, edge enhancement is performed for the band-pass directional subbands by a nonlinear gain function. While the coefficients of low-pass subbands are adjusted by the gain function based on a gray-scale transform and the local mean. The gray-scale transform aims to expand the dark areas of digital holographic image. The undetermined parameters are found by uniform searching particle swarm optimization. The fitness function takes into account the contrast, definition and peak signal-to-noise ratio of image. A large number of experimental results show that, compared with three existing enhancement methods, the proposed method can more effectively improve the contrast and definition of reconstructed image in digital holography, highlight edges and textures, and suppress speckle noise. As a result, the measurement accuracy of digital holography can be improved.

引用

共 22 条

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