Abstract This research proposes anAdaptive Weighted Fuzzy Mean Filter(AWFMF)basedonCloud Model (CM)to remove the saltandpepper noise in the digital images. Also,the performance of the proposed filter is compared with existing variants of median and switching filters using peak signal to noise ratio(PSNR)and quality index.The proposed filter is able to remove saltandpepper noise even at 90% noiselevel with good detail preservation.

References

[1]Beevi Z.and Sathik Mohamed., A Robust Segmentation Approach for Noisy Medical Images Using Fuzzy Clustering With Spatial Probability, The International Arab Journal of Information Technology,vol. 9, no. 1, 2pp. 74- 83, 012.

[2]Brownrigg D., TheWeighted Median Filter, Communicationsof the ACM,vol. 27,no. 8, pp. 807-818, 1984.

[3]Chan R., Ho C.,and Nikolova M., Salt-and- Pepper Noise RemovalbyMedian-Type Noise DetectorsandDetail-Preserving Regularization, IEEE Transactions on Image Processing,vol. 14, no. 10, pp.1479-1485, 2005.

[4]Chao Z., Qian C., Xiubao S., and Jianle R., Brightness Preserving Image Contrast Enhancement using Spatially Weighted Histogram Equalization, TheInternational Arab Journal of Information Technology,vol. 11,no. 1,pp. 25-33,2014.

[5]Chen H. and Li B., QualitativeRules Mining andReasoningbased onCloud Model, in Proceedings of the 2ndInternational Conference on Software Engineering and Data Mining, Chengdu,pp.523-526, 2010.

[6]Chen T., Ma K., and Chen L., Tri-State Median FilterforImage Denoising, IEEE Transactions on Image Processing, vol8,no. 12, pp.1834- 1838, 1999.

[7]Gao Y., AnOptimization Algorithmbased on Cloud Model, in Proceedings of International Conference on Computational Intelligence and Security,Beijing, pp. 84-87, 2009.

[8]Gonzalez R.and Woods R.,Digital Image Processing,Prentice Hall,2002.

[9]Gonzalo R. and Russel E., Detail Preserving Rank Order based Filters for Image Processing, IEEE Transactions onAcoustics, Speechand Signal Processing, vol. 37, no. 1,pp. 83-98, 1989.

[10]Hwang H.and Haddad R. A., AdaptiveMedian Filters: NewAlgorithmsandResults, IEEE Transactions on Image Processing,vol.4,no. 4, pp. 499-502, 1995.

[11]Ko S. and Lee S., CenterWeighted Median Filtersand theirApplicationstoImage Enhancement, IEEETransactions on Circuits and Systems,vol. 38,no. 9, pp. 984-993, 1991.

[12]Li D., Liu C., and Gan W., ANew Cognitive Model:Cloud Model, International Journal on Intelligence Systems, vol. 24, no. 3, pp. 357-375, 2009.

[13]Ng P. and Ma K., ASwitching Median Filter withBoundary Discriminative Noise Detection forExtremely Corrupted Images, IEEE An Adaptive Weighted Fuzzy Mean Filter Based on Cloud Model613 Transactions on Image Processing,vol. 15,no. 6, pp. 1506-1516, 2006.

[14]Qi Y., Classification forTrademark Image based onNormal Cloud Model, inProceedings of International Conference on Information Management, Innovation Management and Industrial Engineering,Xi'an,pp. 74-77,2009.

[15]Qin K., Xu K., Du Y., and Li D., AnImage Segmentation Approachbased onHistogram Analysis Utilizing Cloud Model, inProceedings ofthe 7thInternational Conference on Fuzzy Systems and Knowledge Discovery,Yantai, pp. 524-528, 2010.

[16]Shi Y. and Yu X., ImageSegmentation Algorithmbased onCloud ModeltheApplication of fMRI, in Proceedings ofInternational ConferenceonIntelligent Computation Technology and Automation,Hunan, pp. 136- 140, 2008.

[17]Srinivasan K.and Ebenezer D., ANew Fastand Efficient DecisionbasedAlgorithmforRemoval ofHigh-Density Impulse Noises, IEEE Signal Processing Letters,vol. 14,no. 3, pp. 189-192, 2007.

[18]Wang H.and Deng Y., SpatialClustering Methodbased onCloud Model, inProceedings ofthe 4thInternational Conference on Fuzzy Systems and Knowledge Discovery,Haikou, pp. 272-276, 2007.

[19]Wang Z. and Zhang D., ProgressiveSwitching Median Filterfor theRemovalofImpulse Noise fromHighly Corrupted Images, IEEE Transactionson Circuitsand Systems II, Analog Digital Signal Processing,vol.46,no. 1, pp. 78- 80, 1999.

[20]Yin L., Yang R., Gabbouj M., and Neuvo Y., WeightedMedian Filters:ATutorial, IEEE Transactions on Circuits and Systems II, Analog and Digital SignalProcessing,vol. 43,no. 3, pp. 157-192, 1996.

[21]Zhou W.andBovikA., AUniversal Image Quality Index, IEEE Signal Processing Letters, vol. 9,no.3, pp. 81-84, 2002.

[22]Zhou Z., Cognition and Removal of Impulse Noise with Uncertainty, IEEE Transactions on Image Processing,vol. 21, no. 7, pp. 3157-3167, 2012. Kannan Kanagarajreceived his PhD Degree in the area of Digital Image Processing from Manonmaniam Sundaranar University in the year 2014. He received his Master of Engineering Degree in Industrial Engineering from Anna University and Bachelor of Engineering Degree in Electronics and Communication Engineering from Madurai Kamaraj University. He is in the field of teaching since 1999. At present, he is an Associate Professor in the department of Mechanical Engineering of Kamaraj College of Engineering and Technology, Virudhunagar. His area of interest includes Signal Processing, Image Processing, Embedded System and RTOS. He published many technical papers in NationalandInternational JournalsandConferences. He is a life member of ISTE, IETE, BES, IAE and IACSIT.