The week's pick
Reseach Article
Wavelet-based Image Enhancement Techniques for Improving Visual Quality of Ultrasonic Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 39 - Number 17 |
| Year of Publication: 2012 |
| Authors: K. Karthikeyan, C. Chandrasekar |
10.5120/4916-7488
|
K. Karthikeyan, C. Chandrasekar . Wavelet-based Image Enhancement Techniques for Improving Visual Quality of Ultrasonic Images. International Journal of Computer Applications. 39, 17 ( February 2012), 49-53. DOI=10.5120/4916-7488
Abstract
Medical imaging is concerned with the development of the imaging devices that help to identify different aspects of the tissue and organs based on various properties and reveal new properties of the tissue and internal structure. Ultrasonic devices are frequently used for medical imaging and the images produced by these devices often have to be converted to a form that is better suited for image analysis and understanding, which are referred as ‘image enhancement techniques’. In this paper, three techniques are proposed for edge enhancement, image enlargement and image fusion. All the algorithms have the common goal of improving the visual quality of ultrasonic images and are based wavelets and other image processing techniques. The proposed models were tested vigorously using various test images obtained and the experimental results proved that the proposed models produce significant improvement over the existing traditional systems.
References
- Cha, Y. and Kim, S. (2007), The error-amended sharp edge (EASE) scheme for image, IEEE Transactions on Image Processing, Vol. 16, No. 6, pp. 1496–1606.
- Chanda, B. and Majumder, D.D. (2002), An edge preserving noise smoothing technique using multiscale morphology, Signal Processing, Elsevier North-Holland, Inc. Amsterdam, The Netherlands, Vol. 82, No. 4, pp. 527-544.
- Chang, S.G., Cvetkovic, Z. and Vetterli, M. (2006), Locally adaptive wavelet-based image interpolation, IEEE Transactions on Image Processing, Vol. 15, No. 6, pp. 479–482.
- Hangiandreou, N.J. (2003), Physics Tutorial for Residents: Topics in US: B-mode US: Basic Concepts and New Technology – Hangiandreou, Radiographics, Vol. 23, No.4, p. 1019.
- Hill, P. (2002), Wavelet Based Texture Analysis and Segmentation for Image Retrieval and Fusion, PhD thesis, Department of Electrical and Electronic Engineering, University of Bristol, UK.
- Karthikeyan, K. and Chandrasekar, C. (2010), Speckle Noise Reduction Techniques for Ultrasonic Image Enhancement - A Literature study”, International Journal of Emerging Technologies and Applications in Engineering, Technology and Sciences (IJ-ETA-ETS), Vol. 3, Issue. 2, pp. 515–519.
- Karthikeyan, K. and Chandrasekar, C. (2010), A Study on the Application of Wavelets for Despeckling Ultrasound Images, International Journal of Computer Information Systems, Silicon Valley Publications, UK, Vol. 1, No. 5, pp: 48–54.
- Karthikeyan, K. and Chandrasekar, C. (2011), Speckle noise reduction of medical ultrasound images using Bayesshrink Wavelet threshold, International Journal of Computer Applications (IJCA, New York), Vol. 22, Number 9.
- Li, H., Manjunath, S. and Mitra, S. (1995), Multisensor image fusion using the wavelet transform. Graphical Models and Image Processing, Vol. 57, No.3, pp.235–245.
- Li, X. and Orchard, M.T. (2001), New edge-directed interpolation, IEEE Transactions on Image Processing, Vol. 10, No. 10, pp. 1521–1527.
- Lin, C.T., Fan, K.W., Pu, H.C., Lu, S.M. and Liang, S.F. (2007), An HVS-directed neural-network-based image resolution enhancement scheme for image resizing, IEEE Transactions on Fuzzy Systems, Vol. 15, No. 4, pp. 605–615.
- Matuszewski, B., Shark, L.K. and Varley, M. (2000), Region-based wavelet fusion of ultrasonic, radiographic and shearographyc non-destructive testing images, Proceedings of the 15th World Conference on Non-Destructive Testing, Rome.
- Morse, B.S. and Schwartzwald, D. (1998), Isophote-based interpolation, Proceedings of the IEEE International Conference on Image Processing, Chicago, Ill, USA, Vol. 3, pp. 227–231.
- Nikolov, S., Hill, P., Bull, D. and Canagarajah, N. (2001), Wavelets for image fusion. In A. Petrosian and F. Meyer, editors, Wavelets in Signal and Image Analysis, Computational Imaging and Vision Series, Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 213–244.
- Piella, G. (2002), A region-based multiresolution image fusion algorithm. In ISIF Fusion 2002 conference, Annapolis.
- Piella, G. (2003), A general framework for multiresolution image fusion: from pixels to regions. Information Fusion, Vol.4, pp.259–280.
- Pratt, W.K. (2007), Digital Image Processing : PKIS Scientific Inside, 4th Edition, John Wiley & Sons, Inc., New York.
- Reeves, T. and Jernigan, M. (1997), Multiscale-based Image enhancement, Canadian Conference on Electrical and Computer Engineering, Vol. 2, pp.500-505.
- Sudha, S., Suresh, G.R. and Sukanesh, R. (2009), Comparative Study on Speckle Noise Suppression Techniques for Ultrasound Images, International Journal of Engineering and Technology Vol. 1, No. 1, pp. 1793-8236.
- Temizel, A. and Vlachos, T. (2006), Wavelet domain image resolution enhancement, IEEE Proceedings Vision, Image and Signal Processing, Vol. 153, No. 1, pp. 25–30.
- Tso, B. and Mather, P. (2009), Classification Methods for Remotely Sensed Data (2nd ed.), CRC Press, pp. 37–38.
- Wang, Q. and Ward, R.K. (2007), A new orientation-adaptive interpolation method, IEEE Transactions on Image Processing, Vol. 16, No. 4, pp. 889–900.
- Wilson, T., Rogers, S. and Kabrisky, M. (1995), Perceptual based hyperspectral image fusion using multi-spectral analysis. Optical Engineering, Vol.34, No.11, pp. 3154–3164.
- www.wikipedia.org
- Xu, K., Zheng, X. and Cheng, X. (1999), A novel method for image enhancement of medical images based on wavelet, Acta Electronica Sinica, Vol. 27, No. 9, pp. 121–123.
- Zhang, L. and Wu, X. (2006), An edge-guided image interpolation algorithm via directional filtering and data fusion, IEEE Transactions on Image Processing, Vol. 15, No. 8, pp. 2226–2238.
- Zhang, X. and Wu, X. (2008) Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation, IEEE Transactions on Image Processing, Vol. 17, No. 6, pp. 887–896.
Index Terms
Keywords