Noise Removal Using HWD Implemented by Dmeyer and Kaiser Window
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In the present era, transfer of digital images via communication channel is affected by noise. Received images need to be processed so that noise is eliminated, which requires information about the noise and the image. Noise is an unwanted signal that interferes with the original signal and reduces the quality of the digital image. In this article, a noise elimination algorithm is applied where the image is preserved by preservation of the edges and image texture details, without fading during the image smoothing process. Eliminating of the noise from the image by preserving the edges is becoming one of the researched after topic in digital image transfer. Many noise elimination techniques have been developed for image processing and computer visual communities. Although these methods appear to be very different by using compound filter banks to create an uncompromising feature to maintain meaningful edges, we find better results than other traditional methods. In this article, we have removed the noise filter relatively and efficiently using the Dmeyer Wavelets Transform, Hybrid Wavelets Directional and Wavelet transforms by applying the Caesar window, and improved the edges of the image.
KeywordsDenoising algorithms Wavelet filter bank Quincunx diamond filter bank Kaiser window Dmeyer
- 3.Candes, E. J., & Donoho, D. L. (1999). Curvelets—A surprisingly effective nonadaptive representation for objects with edges. In A. Cohen, C. Rabut, & L. L. Schumaker (Eds.), Curve and surface fitting. Nashville, TN: Vanderbuilt Univ. Press.Google Scholar
- 6.Sendur, L., & Selesnick, I. W. (2005). New image transforms using hybrid wavelets and directional filter banks: Analysis and design. In Proceedings of IEEE international conference on image processing, Genova, Italy (Vol. 1, pp. 733–736).Google Scholar
- 7.Bamberger, R. H. (1993). New results on two and three dimensional directional filter banks. In Proceedings of Asilomar conference on signals, systems, and computers (Vol. 2, pp. 1286–1290).Google Scholar
- 14.Xudong, T., Xinyuan, L., Yiqing, D., & Jianru, L. (2015). Design of orthonormal filter banks based on meyer wavelet. (IJACSA) International Journal of Advanced Computer Science and Applications, 6(7), 109–112.Google Scholar