Абстрактный

Image Denoising Method Using curvelet Transform and Wiener Filter

A. Anilet Bala, Chiranjeeb Hati and CH Punith

A new image denoising method based on curvelet transform is proposed. The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. Here, we pursue "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. Denoising of an image is done by processing an image through Wiener filter and using curvelet transform [1], [6]. Experimental results show that proposed denoising technique performs better in terms of the PSNR. We have compared PSNR values of proposed algorithm with that of wavelet and curvelet in RBG and YCbCr regions.