An Efficient Gaussian Noise Removal Image Enhancement Technique for Gray Scale Images
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.
[1] K, N. Plataniotis and A. N. Venetsanopoulos, Color Image Processing
and Applications. Berlin, Germany: Springer, 2000.
[2] R. Lukac, B. Smolka, K. Martin, K. N. Plataniotis, and A. N.
Venetsanopoulos, “Vector filtering for color imaging,” IEEE Signal
Process. Mag., vol. 22, no. 1, pp. 74–86, Jan. 2005.
[3] R. Lukac, and K. N. Plataniotis, “A taxonomy of color image filtering
and enhancement solutions,” in Advances in Imaging and Electron
Physics, P. W. Hawkes, Ed. New York: Elsevier, 2006, vol. 140,
pp.187–264.
[4] Buyue, Zhang, Member, IEEE, and Jan P. Allebach, Fellow, IEEE
“Adaptive Bilateral Filter for Sharpness Enhancement and Noise
Removal” IEEE Transactions on Image Processing, Vol. 17, No. 5, May
2008
[5] Samuel Morillas, Valentín Gregori, and Antonio Hervás “Fuzzy Peer
Groups for Reducing Mixed Gaussian-Impulse Noise From Color
Images” IEEE Transactions on Image Processing, Vol. 18, No. 7, July
2009
[6] Chih-Hsing Lin, Jia-Shiuan Tsai, and Ching-Te Chiu “Switching
Bilateral Filter With a Texture/Noise Detector for Universal Noise
Removal” IEEE Transactions on Image Processing, Vol. 19, No. 9,
September 2010 2307
[7] Punyaban Patel, Bibekananda Jena, Banshidhar Maji, “Fuzzy based
Adaptive mean filtering techniques for removal of impulse noise from
images”, International journal of Computer Vision and Signal
Processing”,Vol(1),15-21,2012.
[8] Aher, Jodhanle “Removal of Mixed Impulse Noise and Gaussian Noise
Using Genetic Programming”, IEEE con. Image processing 978-1-4673-
1714-6-2012.
[9] Joan-Gerard Camarena, Valent´ın Gregori, Samuel Morillas, and
Almanzor Sapena “A Simple Fuzzy Method to Remove Mixed
Gaussian-Impulsive Noise from Color Images” IEEE Transactions on
Fuzzy Systems, Vol. 21, no. 5, October 2013.
[10] V.Murugan, T. Avudaiappan and R. Balasubramanian, “Implementation
of MRI Brain Image Enhancement Techniques Using Parallel Processing
On Clustering Environment”, Australian Journal of Basic and Applied
Sciences, 8(13), Pages: 390-402, August 2014.
[11] S.Lim, Jae, Two-Dimensional Signal and Image Processing, Englewood
Cliffs, NJ, Prentice Hall, 1990, p. 548, equations 9.44 -- 9.46.
[1] K, N. Plataniotis and A. N. Venetsanopoulos, Color Image Processing
and Applications. Berlin, Germany: Springer, 2000.
[2] R. Lukac, B. Smolka, K. Martin, K. N. Plataniotis, and A. N.
Venetsanopoulos, “Vector filtering for color imaging,” IEEE Signal
Process. Mag., vol. 22, no. 1, pp. 74–86, Jan. 2005.
[3] R. Lukac, and K. N. Plataniotis, “A taxonomy of color image filtering
and enhancement solutions,” in Advances in Imaging and Electron
Physics, P. W. Hawkes, Ed. New York: Elsevier, 2006, vol. 140,
pp.187–264.
[4] Buyue, Zhang, Member, IEEE, and Jan P. Allebach, Fellow, IEEE
“Adaptive Bilateral Filter for Sharpness Enhancement and Noise
Removal” IEEE Transactions on Image Processing, Vol. 17, No. 5, May
2008
[5] Samuel Morillas, Valentín Gregori, and Antonio Hervás “Fuzzy Peer
Groups for Reducing Mixed Gaussian-Impulse Noise From Color
Images” IEEE Transactions on Image Processing, Vol. 18, No. 7, July
2009
[6] Chih-Hsing Lin, Jia-Shiuan Tsai, and Ching-Te Chiu “Switching
Bilateral Filter With a Texture/Noise Detector for Universal Noise
Removal” IEEE Transactions on Image Processing, Vol. 19, No. 9,
September 2010 2307
[7] Punyaban Patel, Bibekananda Jena, Banshidhar Maji, “Fuzzy based
Adaptive mean filtering techniques for removal of impulse noise from
images”, International journal of Computer Vision and Signal
Processing”,Vol(1),15-21,2012.
[8] Aher, Jodhanle “Removal of Mixed Impulse Noise and Gaussian Noise
Using Genetic Programming”, IEEE con. Image processing 978-1-4673-
1714-6-2012.
[9] Joan-Gerard Camarena, Valent´ın Gregori, Samuel Morillas, and
Almanzor Sapena “A Simple Fuzzy Method to Remove Mixed
Gaussian-Impulsive Noise from Color Images” IEEE Transactions on
Fuzzy Systems, Vol. 21, no. 5, October 2013.
[10] V.Murugan, T. Avudaiappan and R. Balasubramanian, “Implementation
of MRI Brain Image Enhancement Techniques Using Parallel Processing
On Clustering Environment”, Australian Journal of Basic and Applied
Sciences, 8(13), Pages: 390-402, August 2014.
[11] S.Lim, Jae, Two-Dimensional Signal and Image Processing, Englewood
Cliffs, NJ, Prentice Hall, 1990, p. 548, equations 9.44 -- 9.46.
@article{"International Journal of Information, Control and Computer Sciences:69835", author = "V. Murugan and R. Balasubramanian", title = "An Efficient Gaussian Noise Removal Image Enhancement Technique for Gray Scale Images ", 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.
", keywords = "Gaussian noise, adaptive bilateral filter, fuzzy peer
group filter, switching bilateral filter, PSNR", volume = "9", number = "3", pages = "784-5", }
