An Adaptive Threshold Method Based on the Local Energy of NSCT Coefficients for Image Denoising

被引:0
|
作者
Liu Xiyu [1 ]
Yao Xiaolan [1 ]
Chen Xin [2 ]
机构
[1] Beijing Inst Technol, Sch Automat, Jinan, Peoples R China
[2] Jinan Diesel Engine Co Ltd, Jinan, Peoples R China
关键词
Nonsubsampled Contour let transform; Adaptive threshold; Image de-noising; Translation invariance; Local energy; CONTOURLET TRANSFORM;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a new adaptive denoising method based on nonsubsampled Contour let transform(NSCT). Traditional Wavelet provides only three directional components so that its geometrical property is not well, and Contour let transform lacks translation invariance, therefore NSCT is developed. The proposed algorithm can adapt different thresholds on different scales and different directions. Further more, we use different thresholds in a directional subband according to local energy of NSCT coefficients to overcome the disadvantages of the unified threshold de-noising method and other fixed thresholds, which cause the image fuzzy distortion because of "over-killed". The experimental results prove that the algorithm outperforms existing schemes in both peak-signal-to-noise-ratio (PSNR) and visual quality.
引用
收藏
页码:279 / +
页数:3
相关论文
共 50 条
  • [41] Wavelet Denoising of Remote Sensing Image Based on Adaptive Threshold Function
    Ma, Yuqing
    Zhu, Juan
    Huang, Jipeng
    ICVIP 2019: PROCEEDINGS OF 2019 3RD INTERNATIONAL CONFERENCE ON VIDEO AND IMAGE PROCESSING, 2019, : 256 - 261
  • [42] Image denoising with window shrink wavelet coefficients by adaptive threshold - art. no. 678613
    Zhao, Yifan
    Li, Jiuxian
    Xia, Liangzheng
    MIPPR 2007: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS; AND MULTISPECTRAL IMAGE ACQUISITION, PTS 1 AND 2, 2007, 6786 : 78613 - 78613
  • [43] A new image denoising method based on the dependency wavelet coefficients
    Zhang, EH
    Huang, SY
    PROCEEDINGS OF THE 2004 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2004, : 3841 - 3844
  • [44] An adaptive denoising method based on local mode estimation
    Wang, Yuehong
    Sun, Xusheng
    Zhang, Jin
    Rong, Gang
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 6555 - 6558
  • [45] Image denoising method based on improved wavelet threshold algorithm
    Zhu, Guowu
    Liu, Bingyou
    Yang, Pan
    Fan, Xuan
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (26) : 67997 - 68011
  • [46] Ultrasonic Liver Image Denoising Based on A Hybrid Threshold Method
    Zhu, H. J.
    Rao, L.
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON POWER ELECTRONICS AND ENERGY ENGINEERING (PEEE 2015), 2015, 20 : 139 - 142
  • [47] An adaptive weighted image denoising method based on morphology
    Wang J.
    Duan S.
    Zhou Q.
    International Journal of Circuits, Systems and Signal Processing, 2021, 15 : 271 - 279
  • [48] Image Denoising Method Based on Improved Wavelet Threshold Transform
    Xi Jianhui
    Tang Li
    2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019), 2019, : 1064 - 1067
  • [49] A new adaptive threshold method for FMDFB Gaussian subbands for image denoising application
    Leavline, E. Jebamalar
    Sutha, S.
    Singh, D. Asir Antony Gnana
    OPTOELECTRONICS AND ADVANCED MATERIALS-RAPID COMMUNICATIONS, 2015, 9 (9-10): : 1315 - 1321
  • [50] Subsquarewise Threshold based Image Denoising
    Pan, Xiaoying
    Chen, Xinfu
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 613 - +