Extremum Median Filter Map Denoising Algorithm Based on Energy Function

WANG Min; ZHAO Jinyu; CHEN Tao; CUI Bochuan; GAO Yang

doi:10.11999/JEIT160955

Volume 39 Issue 6

Jun. 2017

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(6): 1387-1393

WANG Min, ZHAO Jinyu, CHEN Tao, CUI Bochuan, GAO Yang. Extremum Median Filter Map Denoising Algorithm Based on Energy Function[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1387-1393. doi: 10.11999/JEIT160955

Citation:

WANG Min, ZHAO Jinyu, CHEN Tao, CUI Bochuan, GAO Yang. Extremum Median Filter Map Denoising Algorithm Based on Energy Function[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1387-1393. doi: 10.11999/JEIT160955

Citation:

PDF( 5359 KB)

Extremum Median Filter Map Denoising Algorithm Based on Energy Function

doi: 10.11999/JEIT160955

1.
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)

Received Date: 2016-09-22
Rev Recd Date: 2017-02-15
Publish Date: 2017-06-19

Abstract

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)

FullText(HTML)

References(30)

References

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.

Relative Articles

Supplements(0)

Cited By

Proportional views