Min-Max Average Pooling Based Filter for Impulse Noise Removal

被引:41
作者
Satti, Piyush [1 ]
Sharma, Nikhil [1 ]
Garg, Bharat [1 ]
机构
[1] Thapar Inst Engn & Technol, Dept Elect & Commun Engn, Patiala 147001, Punjab, India
关键词
Noise measurement; Image restoration; Image edge detection; Benchmark testing; Correlation; PSNR; Noise reduction; Mean filters; median filters; salt and pepper noise; pooling; image restoration and de-noising; HIGH-DENSITY SALT; PEPPER NOISE; MEAN FILTER;
D O I
10.1109/LSP.2020.3016868
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Image corruption is a common phenomenon which occurs due to electromagnetic interference, and electric signal instabilities in a system. In this letter, a novel multi procedure Min-Max Average Pooling based Filter is proposed for removal of salt, and pepper noise that betide during transmission. The first procedure functions as a pre-processing step that activates for images with low noise corruption. In latter procedure, the noisy image is divided into two instances, and passed through multiple layers of max, and min pooling which allow restoration of intensity transitions in an image. The final procedure recombines the parallel processed images from the previous procedures, and performs average pooling to remove all residual noise. Experimental results were obtained using MATLAB software, and show that the proposed filter significantly improves edges over exiting literature. Moreover, Peak Signal to Noise Ratio was improved by 1.2 dB in de-noising of medical images corrupted by medium to high noise densities.
引用
收藏
页码:1475 / 1479
页数:5
相关论文
共 12 条
[1]   A New Adaptive Switching Median Filter [J].
Akkoul, Smail ;
Ledee, Roger ;
Leconge, Remy ;
Harba, Rachid .
IEEE SIGNAL PROCESSING LETTERS, 2010, 17 (06) :587-590
[2]   Image Blind Denoising With Generative Adversarial Network Based Noise Modeling [J].
Chen, Jingwen ;
Chen, Jiawei ;
Chao, Hongyang ;
Yang, Ming .
2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2018, :3155-3164
[3]   A weighted mean filter with spatial-bias elimination for impulse noise removal [J].
Kandemir, Cengiz ;
Kalyoncu, Cem ;
Toygar, Onsen .
DIGITAL SIGNAL PROCESSING, 2015, 46 :164-174
[4]   Densely connected network for impulse noise removal [J].
Li, Guanyu ;
Xu, Xiaoling ;
Zhang, Minghui ;
Liu, Qiegen .
PATTERN ANALYSIS AND APPLICATIONS, 2020, 23 (03) :1263-1275
[5]  
Liu SongTao Liu SongTao, 2019, Journal of Agricultural Science (Toronto), V11, P1, DOI 10.5539/jas.v11n8p1
[6]   Removal of salt-and-pepper noise in corrupted image using three-values-weighted approach with variable-size window [J].
Lu, Ching-Ta ;
Chen, Yung-Yue ;
Wang, Ling-Ling ;
Chang, Chun-Fan .
PATTERN RECOGNITION LETTERS, 2016, 80 :188-199
[7]  
Patel Punyaban, 2012, International Journal of Image, Graphics and Signal Processing, V4, P53, DOI 10.5815/ijigsp.2012.11.08
[8]   Impulse noise removal using SVM classification based fuzzy filter from gray scale images [J].
Roy, Amarjit ;
Singha, Joyeeta ;
Devi, Salam Shuleenda ;
Laskar, Rabul Hussain .
SIGNAL PROCESSING, 2016, 128 :262-273
[9]  
Shipeng Zhu, 2019, Pattern Recognition and Computer Vision. Second Chinese Conference, PRCV 2019. Proceedings. Lecture Notes in Computer Science (LNCS 11858), P241, DOI 10.1007/978-3-030-31723-2_21
[10]   Recursive cubic spline interpolation filter approach for the removal of high density salt-and-pepper noise [J].
Veerakumar, T. ;
Esakkirajan, S. ;
Vennila, Ila .
SIGNAL IMAGE AND VIDEO PROCESSING, 2014, 8 (01) :159-168