Image Denoising Based on Adaptive and Multi-frame Averaging Filtering

被引:3
|
作者
Xie Qinlan [1 ]
Chen Hong [2 ]
机构
[1] South Cent Univ Nationalities, Coll Elect & Informat Engn, Wuhan, Peoples R China
[2] South Cent Univ Nationalites, Coll Chem & Mat, Wuhan, Peoples R China
关键词
Adaptive image filtering; Bilateral filtering; Steering kernel filtering; Multi-frame averaging filtering; Image denoising;
D O I
10.1109/AICI.2009.490
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To deal with some problem of existing single-frame denoising methods, a adaptive spatial filtering method for denoising of multi-fame images is presented. Firstly each frame is processed by adaptive filters to suppressive noise and to preserve the edge simultaneity. Then each frame of image is filtered by averaging the same pixels of multi-frame to denoise fartherly and alleviate the cartoon-like impacts. Three filters including adaptive filtering on signal-frame, simple mean filtering of multi-frame, and adaptive filtering combined with averaging filtering, are tested by two experiments. The results show that the latter improved the performance of denoising compared with the former two methods.
引用
收藏
页码:523 / +
页数:2
相关论文
共 50 条
  • [31] MMDM: Multi-frame and Multi-scale for Image Demoireing
    Liu, Shuai
    Li, Chenghua
    Nan, Nan
    Zong, Ziyao
    Song, Ruixia
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), 2020, : 1751 - 1759
  • [33] A posterior mean approach for MRF-based spatially adaptive multi-frame image super-resolution
    Shao, Wen-Ze
    Deng, Hai-Song
    Wei, Zhi-Hui
    SIGNAL IMAGE AND VIDEO PROCESSING, 2015, 9 (02) : 437 - 449
  • [34] DEEP MULTI-FRAME MVDR FILTERING FOR BINAURAL NOISE REDUCTION
    Tammen, Marvin
    Doclo, Simon
    2022 INTERNATIONAL WORKSHOP ON ACOUSTIC SIGNAL ENHANCEMENT (IWAENC 2022), 2022,
  • [35] Multi-frame iteration blind deconvolution algorithm based on improved expectation maximization for adaptive optics image restoration
    Zhang, Li-Juan
    Yang, Jin-Hua
    Su, Wei
    Jiang, Cheng-Hao
    Wang, Xiao-Kun
    Tan, Fang
    Zhang, Li-Juan, 1765, China Ordnance Industry Corporation (35): : 1765 - 1773
  • [36] Image Denoising with Adaptive Weighted Graph Filtering
    Chen, Ying
    Tang, Yibin
    Zhou, Lin
    Zhou, Yan
    Zhu, Jinxiu
    Zhao, Li
    CMC-COMPUTERS MATERIALS & CONTINUA, 2020, 64 (02): : 1219 - 1232
  • [37] Self-supervised training for blind multi-frame video denoising
    Dewil, Valery
    Anger, Jeremy
    Davy, Axel
    Ehret, Thibaud
    Facciolo, Gabriele
    Arias, Pablo
    2021 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION WACV 2021, 2021, : 2723 - 2733
  • [38] Sparse representation based multi-frame image super-resolution reconstruction using adaptive weighted features
    Nandi, Debashis
    Karmakar, Jayashree
    Kumar, Amish
    Mandal, Mrinal Kanti
    IET IMAGE PROCESSING, 2019, 13 (04) : 663 - 672
  • [39] Adaptive filtering for color image sharpening and denoising
    Horiuchi, Takahiko
    Watanabe, Kunio
    Tominaga, Shoji
    14TH INTERNATIONAL CONFERENCE ON IMAGE ANALYSIS AND PROCESSING WORKSHOPS, PROCEEDINGS, 2007, : 196 - 201
  • [40] Adaptive Dynamic Filtering Network for Image Denoising
    Shen, Hao
    Zhao, Zhong-Qiu
    Zhang, Wandi
    THIRTY-SEVENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 37 NO 2, 2023, : 2227 - 2235