{"title":"An Efficient Gaussian Noise Removal Image Enhancement Technique for Gray Scale Images ","authors":"V. Murugan, R. Balasubramanian","volume":99,"journal":"International Journal of Computer and Information Engineering","pagesStart":790,"pagesEnd":795,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10001316","abstract":"
Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.<\/p>\r\n","references":"[1] K, N. Plataniotis and A. N. Venetsanopoulos, Color Image Processing\r\nand Applications. Berlin, Germany: Springer, 2000.\r\n[2] R. Lukac, B. Smolka, K. Martin, K. N. Plataniotis, and A. N.\r\nVenetsanopoulos, \u201cVector filtering for color imaging,\u201d IEEE Signal\r\nProcess. Mag., vol. 22, no. 1, pp. 74\u201386, Jan. 2005.\r\n[3] R. Lukac, and K. N. Plataniotis, \u201cA taxonomy of color image filtering\r\nand enhancement solutions,\u201d in Advances in Imaging and Electron\r\nPhysics, P. W. Hawkes, Ed. New York: Elsevier, 2006, vol. 140,\r\npp.187\u2013264.\r\n[4] Buyue, Zhang, Member, IEEE, and Jan P. Allebach, Fellow, IEEE\r\n\u201cAdaptive Bilateral Filter for Sharpness Enhancement and Noise\r\nRemoval\u201d IEEE Transactions on Image Processing, Vol. 17, No. 5, May\r\n2008\r\n[5] Samuel Morillas, Valent\u00edn Gregori, and Antonio Herv\u00e1s \u201cFuzzy Peer\r\nGroups for Reducing Mixed Gaussian-Impulse Noise From Color\r\nImages\u201d IEEE Transactions on Image Processing, Vol. 18, No. 7, July\r\n2009\r\n[6] Chih-Hsing Lin, Jia-Shiuan Tsai, and Ching-Te Chiu \u201cSwitching\r\nBilateral Filter With a Texture\/Noise Detector for Universal Noise\r\nRemoval\u201d IEEE Transactions on Image Processing, Vol. 19, No. 9,\r\nSeptember 2010 2307\r\n[7] Punyaban Patel, Bibekananda Jena, Banshidhar Maji, \u201cFuzzy based\r\nAdaptive mean filtering techniques for removal of impulse noise from\r\nimages\u201d, International journal of Computer Vision and Signal\r\nProcessing\u201d,Vol(1),15-21,2012.\r\n[8] Aher, Jodhanle \u201cRemoval of Mixed Impulse Noise and Gaussian Noise\r\nUsing Genetic Programming\u201d, IEEE con. Image processing 978-1-4673-\r\n1714-6-2012.\r\n[9] Joan-Gerard Camarena, Valent\u00b4\u0131n Gregori, Samuel Morillas, and\r\nAlmanzor Sapena \u201cA Simple Fuzzy Method to Remove Mixed\r\nGaussian-Impulsive Noise from Color Images\u201d IEEE Transactions on\r\nFuzzy Systems, Vol. 21, no. 5, October 2013.\r\n[10] V.Murugan, T. Avudaiappan and R. Balasubramanian, \u201cImplementation\r\nof MRI Brain Image Enhancement Techniques Using Parallel Processing\r\nOn Clustering Environment\u201d, Australian Journal of Basic and Applied\r\nSciences, 8(13), Pages: 390-402, August 2014.\r\n[11] S.Lim, Jae, Two-Dimensional Signal and Image Processing, Englewood\r\nCliffs, NJ, Prentice Hall, 1990, p. 548, equations 9.44 -- 9.46. ","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 99, 2015"}