期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2012
卷号：1
期号：4
页码：671-679
出版社：Shri Pannalal Research Institute of Technolgy
摘要：In this paper we propose a new method to reduce noise in digital image. Images corrupted by Gaussian Noise is still a classical problem. To reduce the noise or to improve the quality of image we have used two parameters i.e. quantitative and qualitative. For quantity we will compare peak signal to noise ratio (PSNR). Higher the PSNR better the quality of the image. For quality we compare Visual effect of image. Image denoising is basic work for image processing, analysis and computer vision. The Curvelet transform is a higher dimensional generalization of the Wavelet transform designed to represent images at different scales and different angles.In this paper we proposed a Curvelet Transformation based image denoising, which is combined with Gabour filter in place of the low pass filtering in the transform domain. We demonstrated through simulations with images contaminated by white Gaussian noise.Experimental results show that our proposed method gives comparatively higher peak signal to noise ratio (PSNR) value, are much more efficient and also have less visual artifacts compared to other existing methods.
