Gaussian Noise and Haar Wavelet Transform Image Compression on Transmission of Dermatological Images
Telemedicine provides medical information and services using telecommunication technologies. Teledermatology, is a special part in the medical field of dermatology and one of the most common applications of telemedicine and e-health. Telecommunication technologies are used in Teledermatology to exchange medical information over a distance using audio, visual and data communication. Medical images require compression; Wavelet-based image compression provides substantial improvements in picture quality at higher compression ratios. An ideal image compression system must yield high quality compressed image with high compression ratio; this ratio can be achieved using transform-based image compression, however the contents of the image affects the choice of an optimum compression ratio and the optimum compression method. This paper presents image compression method, Haar wavelet transform, which can be applied to compress dermatology images before the transmission through a communication channel.
KeywordsTelemedicine Teledermatology Haar Wavelet Transform Medical image compression Adaptive White Gaussian Noise (AWGN) Optimum Image Compression
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- 1.Ansari, N., Fong, B., Zhang, Y.T.: Wireless Technology Advances and Challenges for Telemedicine. IEEE Communications Magazine (2006)Google Scholar
- 2.Serener, A., Kavalcioglu, C.: Teledermatology based medical images with AWGN Channel in Wireless Telemedicine System. In: Proceedings of the 1st WSEAS International Conference on Manufacturing Engineering, Quality and Production Systems, pp. 145–150. Brasov, Romania (2009)Google Scholar
- 4.Gonzalez, R., Woods, E.R., Eddins, L.S.: Digital Image Processing. Prentice - Hall, Upper Saddle River (2002)Google Scholar
- 7.Khashman, A., Dimililer, K.: Image compression using Neural Networks and Haar wavelet. WSEAS Trans. On Signal Processing 4(5) (2008)Google Scholar
- 8.Ashok, V., Balakumaran, T., Gowrishankar, C., Vennila, I., Kumar, N.A.: The fast haar wavelet transform for signal & image processing. Int. Jor. Of Comp. Science and Inf. Security 7(1) (2010)Google Scholar
- 9.Bhardwaj, A., Ali, R.: Image Compression using modified fast Haar wavelet transform. World App. Sci. Jor. 7(5), 647–653 (2009)Google Scholar
- 10.Khashman, A., Dimililer, K.: Intelligent System for Medical X-Rays Compression. Trans. On Mass-Data Analysis of Images and Signals 1(1), 3–14 (2009)Google Scholar
- 11.Khashman, A., Dimililer, K.: Comparison Criteria for Optimum Image Compression. In: Proceeding of the IEEE International Conference on ’Computer as a Tool’, pp. 935–938. IEEE Press, Serbia (2005)Google Scholar
- 12.Patidar, P., Gupta, M., Sriyastava, S., Nagawat, A.K.: Image De-noising by Various Filters for Different Noise. Int. J. of Comp. App. 9(4) (2009)Google Scholar