基于能量函数的极值中值滤波星图去噪算法

王敏; 赵金宇; 陈涛; 崔博川; 高扬

doi:10.11999/JEIT160955

基于能量函数的极值中值滤波星图去噪算法

doi: 10.11999/JEIT160955

2.
(中国科学院长春光学精密机械与物理研究所长春 130033) ②(中国科学院大学北京 100049)

基金项目:

国家863计划项目(2011AA8082035)，中国科学院长春光学精密机械与物理研究所三期创新工程资助项目(065X32CN60)

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出版历程
- 收稿日期: 2016-09-22
- 修回日期: 2017-02-15
- 刊出日期: 2017-06-19

Extremum Median Filter Map Denoising Algorithm Based on Energy Function

2.
(Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

Funds:

The National 863 Program of China (2011AA 8082035), The Third Phase of Innovative Engineering Projects of the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (065X32CN60)

摘要

摘要: 利用地基观测相机拍摄的以深空为背景的星图受星空复杂背景的影响，往往具有较高的噪声水平。同时由于星图主要由恒星、空间目标和星空背景噪声组成，且成点状分布，星图目标和噪声呈现较大的相似性，传统的图像去噪算法并不适用于星图。为此，该文提出一种基于能量函数的极值中值滤波去噪算法，该算法在去除星图椒盐噪声的同时能够较好地保持图像目标信息。该方法针对疑似噪声点采用二次检测的方式，并且结合改进的自适应中值滤波和能量函数模型进行灰度值恢复。该文分别使用仿真试验和真实星图处理试验对该方法进行验证，在客观评价中，图像峰值信噪比PSNR(Peak Signal to Noise Ratio)最高可提高3倍多，均方误差MSE(Mean Squared Error)减小为加噪图像的。试验结果表明，该方法可有效地降低传统方法的噪声误检问题，同时提高噪声图像的恢复精度，非常适合星图噪声的去除。
- 星图去噪 /
- 极值中值滤波 /
- 峰值信噪比 /
- 均方差
Abstract: The star maps acquired by the ground-based cameras are susceptible to the complex background of the starry sky and thus have high noise levels. In addition, the targets in star maps are similar to the noises due to their punctate shapes. As a result, the traditional image denoising method is not applicable to star maps. A new adaptive extremum median filtering denoising algorithm is put forward based on energy function, which can effectively remove the salt and pepper noise of the star maps and keep the small target information at the same time. This method employs a twice-check strategy to reduce the false detection ratio of noisy pixels and uses the improved adaptive median filter and the energy function model to recovery noise imagery. The simulated and real star map experiments show that, the Peak Signal to Noise Ratio (PSNR) is improved about 3 times and the Mean Squared Error (MSE) is reduced by in the terms of objective evaluations, the proposed method can effectively improve the denoising result and thus is applicable to star maps.
- Star map denoising /
- Extremum median filter /
- Peak Signal to Noise Ratio (PSNR) /
- Mean Squared Error (MSE)

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参考文献(30)

NIKOLOVA M. A varational approach to remove outliers and impulse noise[J]. Journal of Mathematical Imaging and Version, 2004, 20(1/2): 99-120. doi: 10.1023/B:JMIV. 0000011326.88682.e5.

魏伟, 刘恩海. 红外星图预处理及星点定位精度分析[J]. 红外与激光工程, 2014, 43(3): 991-996. doi: 10.3969/j.issn.1007- 2276.2014.03.057.

WEI Wei and LIU Enhai. Preprocessing of infrared star map and position accuracy analysis of star point[J]. Infrared and Laser Engineerring, 2014, 43(3): 991-996. doi: 10.3969/j.issn. 1007-2276.2014.03.057.

杨卓东, 张欣, 张涛, 等. 改进自适应中值滤波的图像去噪[J]. 通信技术, 2015, 48(11): 1257-1260. doi: 10.3969/j.issn.1002- 0802.2015.11.010.

YANG Zhuodong, ZHANG Xin, ZHANG Tao, et al. Image noise-removal on modified adaptive median filter[J]. Communications Technology, 2015, 48(11): 1257-1260. doi: 10.3969/j.issn.1002-0802.2015.11.0 10.

周玲芳, 陈菲. 基于斜率差值的自适应图像椒盐噪声滤波算法[J]. 液晶与显示, 2015, 30(4): 695-700. doi: 10.3788 /YJYXS20153004.0695.

ZHOU Lingfang and CHEN Fei. Adaptive slope difference algorithm for filtering salt and pepper noise in image[J]. Chinese Journal of Liquid Crystals and Displays, 2015, 30(4): 695-700. doi: 10.3788/YJYXS 20153004.0695.

黄存令, 段锦, 祝勇, 等. 一种改进的极值中值滤波算法[J]. 长春理工大学学报(自然科学版), 2013, 36(3/4): 141-143. doi: 10.3969/j.issn.1672-9870.2013.03.042.

HUANG Cunling, DUAN Jin, ZHU Yong, et al. An improved extremum and median filtering algorithm[J]. Journal of Changchun University of Science and Technology (Natural Science Edition), 2013, 36(3/4): 141-143. doi: 10.3969/j.issn. 1672-9870.2013.03.042.

王红梅, 李言俊, 张科. 基于极值检测的图像滤波算法[J]. 激光与红外, 2007, 37(10): 1117-1119. doi: 10.3969/j.issn.1001- 5078.2007.10.026.

WANG Hongmei, LI Yanjun, and ZHANG Ke. An image filter algorithm based on extremum detection[J]. Laser Infrared, 2007, 37(10): 1117-1119. doi: 10.3969/j.issn.1001- 5078.2007.10.026.

王益艳, 王晅. 基于2级噪声检测的改进中值滤波算法[J]. 计算机工程与设计, 2008, 29(11): 2841-2843. doi: 10.16208 /j.issn1000-7024.2008.11.029.

WANG Yiyan and WANG Xuan. Improved median filter algorithm based on two-stage noise detection[J]. Computer Engineering and Design, 2008, 29(11): 2841-2843. doi: 10.16208/j.issn 1000-7024.2008.11.029.

CHAN R H, HO C W, and NIKOLOVA M. Convergence of Newtons method for a minimization problem in impulsenoise removal[J]. Journal of Computational Mathematics, 2004, 22(2): 168-177.

钟涛, 张建国, 左俊彦. 一种改进的中值滤波算法及其应用[J]. 云南大学学报(自然科学版), 2015, 37(4): 505-510. doi: 10.7540/j.ynu.20140432.

ZHONG Tao, ZHANG Jianguo, and ZUO Junyan. An improvement median filter algorithm and its application[J]. Journal of Yunnan University(Natural Science Edition), 2015, 37(4): 505-510. doi: 10.7540/j.ynu.20140432.

王晓凯, 李锋. 改进的自适应中值滤波[J]. 计算机工程与应用, 2010, 46(3): 175-176. doi: 10.3778/j.issn.1002-8331.2010.03. 053.

WANG Xiaokai and LI Feng. Improved adaptive median filtering[J]. Computer Engineering and Applications, 2010, 46(3): 175-176. doi: 10.3778/j.issn.1002-8331.2010.03.053.

王明佳, 张旭光, 韩广良, 等. 自适应权值滤波消除图像椒盐噪声的方法[J]. 光学精密工程, 2007, 15(5): 779-783. doi: 10.3321/j.issn:1004-924X.2007.05.026.

WANG Mingjia, ZHANG Xuguang, HAN Guangliang, et al. Elimination of impulse noise by auto-adapted weight filter[J]. Optics and Precision Engineering, 2007, 15(5): 779-783. doi: 10.3321/j.issn:1004-924X.2007.05.026.

李阳, 张欣, 张涛, 等. 一种保留图像边缘的自适应中值滤波器算法[J]. 通信技术, 2015, 48(12): 1367-1371. doi: 10.3969 /j.issn.1002-0802.2015.12.010.

LI Yang, ZHANG Xin, ZHANG Tao, et al. An adaptive median filter algorithm for preserving image edges[J]. Communications Technology, 2015, 48(12): 1367-1371. doi: 10.3969/j.issn.1002-0802.2015.12. 010.

CHAN R H, HO C W, and NIKOLOVA M. Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization[J]. IEEE Transactions on Image Processing, 2005, 14(10): 1479-1485. doi: 10.1109/TIP. 2005.852196.

PERREAULT S and HBERT P. Median filtering in constant time[J]. IEEE Transactions on Image Processing, 2007, 16(9): 2389-2394. doi: 10.1109/TIP.2007.902329.

YANG Qingxiong, AHUJA N , and TAN K H. Constant time median and bilateral filtering[J]. International Journal of Computer Vision, 2015, 112(3): 307-318. doi: 10.1007/sl1263- 014-0764-y.

ZHAO Hanli, GAO Dandan, WANG Ming, et al. Real-time edge-aware weighted median filtering on the GPU[J]. Computers Graphics, 2016, 61: 11-18. doi: 10.1016/j.cag. 2016.09.003.

牛秀琴. 几种改进的中值滤波算法研究[D]. [硕士论文], 四川师范大学, 2009: 13-19.

NIU Xiuqin. Research on several improved median filter algorithms[D]. [Master dissertation], Sichuan Normal University, 2009: 13-19.

杨文波, 马天玮, 刘剑. 非局部变分修复法去除高密度椒盐噪声[J]. 中国光学, 2013, 6(6): 876-884. doi: 10.3788/CO. 20130606.0876.

YANG Wenbo, MA Tianwei, and LIU Jian. Elimination of impulse noise by non-local variation inpainting method[J]. Chinese Optics, 2013, 6(6): 876-884. doi: 10.3788/CO. 20130606.0876.

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