A Hybrid Method For Enhancement Of MRI Knee Images
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2013 by IJETT Journal|
|Year of Publication : 2013|
|Authors : U.Pavan Kumar , P.Padmaja|
U.Pavan Kumar , P.Padmaja. "A Hybrid Method For Enhancement Of MRI Knee Images". International Journal of Engineering Trends and Technology (IJETT). V4(10):4348-4351 Oct 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group.
Pre-processing is the basic step to reconstruct the image with some useful feature. This technique is essential for the enhancement of knee images which increases the efficiency of the subsequent tasks of the knee recognition system. In this paper, an hybrid approach is proposed which is a combination of contrast stretching and adaptive thresholding that simultaneously adjusts the intensity level of knee images using boundaries is developed. The validation of proposed system is carried out based on the defined parameter matrices. The experimental results shows that the proposed method proves efficient when compared to other traditional methods.
 M. Sepasian, W. Balachandran and C. Mares, “ Image Enhancement for Fingerprint Minutiae-Based Algorithms Using CLAHE, Standard Deviation Analysis and Sliding Neighborhood”, Proceedings of the World Congress on Engineering and Computer Science 2008 WCECS 2008, October 22 - 24, 2008, San Francisco, USA,
 Zhixin Shi , Srirangaraj Setlur , Venu Govindaraju, “Digital Enhancement of Palm Leaf Manuscript Images using Normalization Techniques”, IEEE conference, Computer Vision, Graphics & Image Processing, 2008, P.687-692.
 Manpreet Kaur, Jasdeep Kaur, Jappreet Kaur, “Survey of Contrast Enhancement Techniques based on Histogram Equalization”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No. 7, 2011, P.138-141.
 David Menotti, Laurent Najman, Jacques Facon, and Arnaldo de A. Araújo, “Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving”, IEEE Transactions on Consumer Electronics, Vol. 53, No. 3, 2007, P.1186-1193.
 R.Sharmila, R. Uma, “A New Approach To Image Contrast Enhancement using Weighted Threshold Histogram Equalization with Improved Switching Median Filter”, International Journal Of Advanced Engineering Sciences and Technologies Vol No. 7, No. 2, 2011, P. 206 – 211.
 Tarek A. Mahmoud, Stephen Marshall, “Medical Image Enhancement Using Threshold Decomposition Driven Adaptive Morphological Filter”, 16th European Signal Processing Conference (EUSIPCO 2008), EURASIP, 2008,
 Raman Maini and Himanshu Aggarwal, “A Comprehensive Review of Image Enhancement Techniques”, Journal of Computing, Vol.2, No. 3, 2010, P.8-13.
 Zhou Wang, Alan.C. Bovik, “ A Universal Quality Index”, IEEE Signal Processing Letters,Vol. 20, 2002,P. 1-4.
 H.D. Cheng, Huijuan Xu, “A novel fuzzy logic approach to contrast enhancement”, Pattern Recognition, Vol. 33, 2000, P.809-819.
 J. Najeer Ahamed, V. Rajamani, “Design of Hybrid Filter for Denoising Images Using Fuzzy Network and Edge Detecting”, American Journal of Scientific Research. No.3,2009, P.5-14.
 Sonia Goyal, Seema, “Region Based Contrast Limited Adaptive HE with Additive Gradient for Contrast Enhancement of Medical Images (MRI)”, International Journal of Soft Computing and Engineering (IJSCE), Vol.1, No.4, 2011, P.154-157.
 Muthu Selvi, Roselin and Dr.Kavitha, “A Hybrid Image Enhancement Technique for Noisy Di Dim Images Using Curvelet and Morphology”, International Journal of Engineering Science and Technology, Vol. 2,No.7, 2010, P. 2997-3002 .
 Jayamala K. Patil1 , Raj Kumar, “Advances In Image Processing For Detection Of Plant Diseases”, Journal of Advanced Bioinformatics Applications and Research, Vol 2, No.2, 2011, P. 135-141.
 Mehmet Sezgin, Bulent Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging, Vol.13, No.1, 2004, P.146–165.
Image enhancement, Histogram equalization, Contrast stretching, intensity adjustment, Adaptive Thresholding.