An Adaptive Fuzzy Switching Filter for Images Corrupted by Impulse Noise

Dr. V.Saradhadevi; Dr.V.Sundaram

An Adaptive Fuzzy Switching Filter for Images Corrupted by Impulse Noise

Dr. V.Saradhadevi * §

Contact

Dr.V.Sundaram

Contact

§ Karpagam University

An Adaptive Fuzzy Switching Filter for Images Corrupted by Impulse Noise

Article Fingerprint

ReserarchID

CSTO272J

An Adaptive Fuzzy Switching Filter for Images Corrupted by Impulse Noise Banner

AI TAKEAWAY

Connecting with the Eternal Ground

Abstract

In digital images, impulse noise (such as salt and pepper noise) detection and removal is an important process as the images are corrupted by those noise because of transmission and acquisition. The main aim of the noise removal is to suppress the noise when preserving the edge information. The median filter and its derivatives are usually used for this purpose. These filtering techniques usually applied to the overall image and modify the pixel value. The modification in pixel values will be performed in unaffected pixels also. Hence the sufficient removal of impulse using this technique will leads to the reduction in quality of images. In this paper, Adaptive Fuzzy Switching Filter is proposed which is based on fuzzy logic for removing the impulse noise from the affected image. The proposed technique involves three phases. The first phase will detect the impulse noise by considering grayscale distribution among neighboring pixels. In the second phase, grayscale values for the pixels are determined based on the values of neighboring pixels. The final phase implements the fuzzy switching for further improvement in the image preservation. The fuzzy membership function used in the proposed technique is half open fuzzy membership function. The experimental result shows that the proposed adaptive fuzzy switching filter has the better capability of removing the impulse noise from the corrupted image.

References

17 Cites in Article

Reference Format

S Schulte,V De Witte,M Nachtegael,D Van Der Weken,E Kerre (2006). Fuzzy Two-Step Filter for Impulse Noise Reduction From Color Images.
Sun Zhong-Gui,Chen Jie,Meng Guang-Wu (2008). An Impulse Noise Image Filter Using Fuzzy Sets.
A Awad,H Man (2008). High performance detection filter for impulse noise removal in images.
Haidi Ibrahim,Nicholas Pik Kong,Theam Ng (2008). Simple adaptive median filter for the removal of impulse noise from highly corrupted images.
D Zhang,Zhuoer Shi,Haixiang Wang,D Kouri,D Hoffman (2000). Nonlinear filtering impulse noise removal from corrupted images.
S-J Ko,Y Lee (1991). Center weighted median filters and their applications to image enhancement.
Tong Sun,Yrjö Neuvo (1994). Detail-preserving median based filters in image processing.
T Chen,H Wu (2001). Adaptive Impulse Detection Using Center-Weighted Median Filters.
E Abreu,M Lightstone,S Mitra,K Arakawa (1996). A new efficient approach for the removal of impulse noise from highly corrupted images.
F Russo,G Ramponi (1996). A Fuzzy Filter for Images Corrupted by Impulse Noise.
Y Choi,R Krishnapuram (1997). A Robust Approach to Image Enhancement Based on Fuzzy Logic.
V Boskovitz,H Guterman (2002). An Adaptive Neuro-Fuzzy System for Automatic Image Segmentation and Edge Detection.
Z Wang,D Zhang (1999). Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Images.
Krishnan Nallaperumal,Justin Varghese,S Saudia,K Arulmozhi,K Velu,S Annam (2006). Salt & Pepper Impulse Noise Removal using Adaptive Switching Median Filter.
G Pok,J Liu,A Nair (2003). Selective Removal of Impulse Noise Based on Homogeneity Level Information.
D Van De Ville,M Nachtegael,D Van Der Weken,E Kerre,W Philips,I Lemahieu (2003). Noise reduction by fuzzy image filtering.
Xin Shoushui Chen,Yang,G Cao (2009). Impulse Noise Suppression with an Augmentation of Ordered Difference Noise Detector and an Adaptive Variational Method.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. V.Saradhadevi, Dr.V.Sundaram. 1970. "An Adaptive Fuzzy Switching Filter for Images Corrupted by Impulse Noise". Global Journal of Computer Science and Technology GJCST Volume 11 (GJCST Volume 11 Issue 4).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 11 Issue 4

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST Classification I.4.3

Submission ReceivedJanuary 7, 2011
Peer Review Double Blind
Handling Editor
Accepted February 3, 2011
Published February 13, 2011

Version of record

v1.2

Issue date

March 13, 2011

Language

English

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Score: 152

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Dr. V.Saradhadevi , Dr.V.Sundaram (PhD/Dr. count: 2)

View Count (all-time): 216

Total Views (Real + Logic): 5214

Total Downloads (simulated): 465

Publish Date: 2011 02, Sun

Monthly Totals (Real + Logic):

Month 1: 49 views
Month 2: 40 views
Month 3: 24 views
Month 4: 39 views
Month 5: 32 views
Month 6: 25 views
Month 7: 40 views
Month 8: 54 views
Month 9: 58 views
Month 10: 37 views
Month 11: 50 views
Month 12: 32 views
Month 13: 29 views
Month 14: 50 views
Month 15: 19 views
Month 16: 37 views
Month 17: 32 views
Month 18: 43 views
Month 19: 35 views
Month 20: 36 views
Month 21: 20 views
Month 22: 28 views
Month 23: 37 views
Month 24: 32 views
Month 25: 33 views
Month 26: 15 views
Month 27: 20 views
Month 28: 31 views
Month 29: 24 views
Month 30: 17 views
Month 31: 15 views
Month 32: 15 views
Month 33: 33 views
Month 34: 28 views
Month 35: 17 views
Month 36: 29 views
Month 37: 32 views
Month 38: 31 views
Month 39: 29 views
Month 40: 32 views
Month 41: 31 views
Month 42: 22 views
Month 43: 21 views
Month 44: 36 views
Month 45: 24 views
Month 46: 36 views
Month 47: 22 views
Month 48: 33 views
Month 49: 28 views
Month 50: 28 views
Month 51: 39 views
Month 52: 23 views
Month 53: 32 views
Month 54: 19 views
Month 55: 35 views
Month 56: 29 views
Month 57: 19 views
Month 58: 42 views
Month 59: 38 views
Month 60: 41 views
Month 61: 39 views
Month 62: 40 views
Month 63: 32 views
Month 64: 37 views
Month 65: 41 views
Month 66: 23 views
Month 67: 45 views
Month 68: 22 views
Month 69: 39 views
Month 70: 31 views
Month 71: 33 views
Month 72: 28 views
Month 73: 24 views
Month 74: 38 views
Month 75: 37 views
Month 76: 17 views
Month 77: 36 views
Month 78: 14 views
Month 79: 28 views
Month 80: 41 views
Month 81: 36 views
Month 82: 34 views
Month 83: 14 views
Month 84: 37 views
Month 85: 43 views
Month 86: 25 views
Month 87: 14 views
Month 88: 23 views
Month 89: 29 views
Month 90: 41 views
Month 91: 41 views
Month 92: 34 views
Month 93: 39 views
Month 94: 44 views
Month 95: 32 views
Month 96: 26 views
Month 97: 35 views
Month 98: 48 views
Month 99: 25 views
Month 100: 35 views
Month 101: 16 views
Month 102: 13 views
Month 103: 36 views
Month 104: 15 views
Month 105: 29 views
Month 106: 36 views
Month 107: 32 views
Month 108: 44 views
Month 109: 27 views
Month 110: 27 views
Month 111: 42 views
Month 112: 19 views
Month 113: 31 views
Month 114: 35 views
Month 115: 45 views
Month 116: 24 views
Month 117: 41 views
Month 118: 16 views
Month 119: 16 views
Month 120: 15 views
Month 121: 44 views
Month 122: 34 views
Month 123: 39 views
Month 124: 15 views
Month 125: 40 views
Month 126: 46 views
Month 127: 47 views
Month 128: 39 views
Month 129: 33 views
Month 130: 16 views
Month 131: 32 views
Month 132: 33 views
Month 133: 21 views
Month 134: 41 views
Month 135: 38 views
Month 136: 31 views
Month 137: 23 views
Month 138: 28 views
Month 139: 45 views
Month 140: 34 views
Month 141: 16 views
Month 142: 29 views
Month 143: 29 views
Month 144: 17 views
Month 145: 41 views
Month 146: 26 views
Month 147: 36 views
Month 148: 37 views
Month 149: 24 views
Month 150: 31 views
Month 151: 31 views
Month 152: 38 views
Month 153: 44 views
Month 154: 43 views
Month 155: 20 views
Month 156: 26 views
Month 157: 25 views
Month 158: 24 views
Month 159: 44 views
Month 160: 29 views
Month 161: 44 views
Month 162: 16 views
Month 163: 34 views
Month 164: 25 views
Month 165: 35 views
Month 166: 40 views
Month 167: 35 views
Month 168: 21 views
Month 169: 12 views
Month 170: 34 views
Month 171: 32 views
Month 172: 36 views
Month 173: 27 views
Month 174: 29 views
Month 175: 33 views
Month 176: 20 views
Month 177: 33 views
Month 178: 25 views
Month 179: 26 views
Month 180: 48 views
Month 181: 43 views
Month 182: 32 views
Month 183: 26 views
Month 184: 29 views
Month 185: 37 views
Month 186: 57 views
Month 187: 53 views
Month 188: 15 views

Total Views: 5.2K

Total Downloads: 465

All Trends