References
[1]. Gonzalez, R.C.,and Woods, R.E (2008). Digital Image
Processing, Prentice Hall, Englewood Cliffs, NJ .
[2]. Pratt W.K, (1978). Digital Image Processing, Wiley, New
York.
[3]. Huang, J.S.,and Tseng, D.H., (1988). “Statistical theory
of edge detection”, Journal of Computer Vision Graphics
Image Processing, pp:337–346.
[4]. Canny,J., (1986). “A computational approach to
edge detection”, IEEE Trans. Pattern Analysis, Machine
Intelligence PAMI-8, pp:679–698.
[5]. Venkatesh,S., and Kitchen, L.J., (1992). “Edge
evaluation using necessary components”, Journal of
Computer vision Graphics Image Processing - Graphical
Models Image Processing, Vol. 54, No. 1, pp:23–30.
[6]. Bovik,A.C.,Huang,T.S., and Munson,D.C.,(1986).
“Nonparametric tests for edge detection in noise”,
Pattern Recognition, Vol. 19, No. 3, pp:209–219.
[7]. Olivier laligant and Frederic (2010). “A Nonlinear
Derivative scheme applied to edge detection”, IEEE
Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No.2. pp. 242-257.
[8]. A. Srikrishna, B. Eswara Reddy and M. Pompapathi,
(2014). ”Non-Linear Noise Suppression Edge Detection
Scheme for Noisy Images”, Proceedings of the IEEE
International Conference on recent advances and
innovations in engineering (ICRAIE - 2014), Organized by
Poornima University, Jaipur. ISBN: 978-1-4799-4041- 7,DOI: 10.1109/ICRAIE.2014.6909192, Publisher: IEEE, pp:1-6.
[9]. Dong Hoon Lim., (2004). “ Robust edge detection in
noisy images”,Journal of Computational Statistics & Data
Analysis 50, pp. 803 – 812.
[10]. Hou, Z., and Koh, T.S., (2003)., “Robust edge
detection”, Pattern Recognition, Vol. 36, pp. 2083–2091.
[11]. Fligner, M.A., and Pollicello, G.E., (1981). “ Robust
rank procedures for the Behrens–Fisher problem”, Journal
of Amand Stat.Assoc. Vol. 76, pp:162–168.
[12]. Zumbo, B.D. and Coulombe, D., (1997).
“Investigation of the robust rank–order test for non–normal
Populations with unequal variances: The case of reaction
time”, Canadian Journal of Experimental Psychology, Vol.
51, pp. 139–149.
[13]. Feltovich, N., (2003)., “Nonparametric tests of
differences in medians : comparison of the
Wilcoxon–Mann–Whitney and robust rank-order tests”,
Exp. Econom, Vol. 6, pp:273–297.
[14]. Kurz, L., and Benteftifa, M.H., (1997). Analysis of
Variance in Statistical Image Processing, Cambridge
University Press, Cambridge.
[15]. J. F. Canny, (1983). "Finding edges and lines in
images", M.I.T. Artificial Intell. Lab., Cambridge, MA, Rep.
Al-TR-720.
[16]. R. M. Haralick, (1982). "Zero-crossings of second
directional derivative edge operator," in SPIE Proc. Robot
Vision, Arlington, VA.
[17]. I. A. Abdou and W. Pratt, (1979). “Quantitative design
and evaluation of enhancement/thresholding edge
detectors”, in Proceedings of the IEEE, Vol. 67, No. 5, pp.
753–766.
[18]. R. J. Beattie, (1984). "Edge detection for semantically based early visual processing", Ph.D.
dissertation, Univ. Edinburgh.
[19]. R. H. Chan, C.W. Ho, and M. Nikolova, (2005). “Saltand-
pepper noise removal by median-type noise
detectors and detail-preserving regularization”, IEEE
Trans. Image Process., Vol. 14, No. 10, pp. 1479–1485.
[20]. P.-E. Ng and K.-K.Ma, (2006). “A switching median
filter with boundary discriminative noise detection for
extremely corrupted images,” IEEE Trans. Image Process.,
Vol. 15, No. 6, pp. 1506–1516.
[21]. K. S. Srinivasan and D. Ebenezer, (2007), “A new fast and efficient decision based algorithm for removal of
highdensity impulse noises,” IEEE Signal Process. Lett., Vol.
14, No.3, pp.189–192.
[22]. T. Nodes and N. Gallagher (1982). “Median filters:
Some modifications and their properties,” IEEE Trans.
Acoust., Speech, Signal Process., Vol. 30, No. 5, pp.
739–746.
[23]. Robert M. Haralick and Linda G Shapiro, (1992).
Computer and Robot Vision, Addison-Wesley publishing
company.Inc, NewYork .