Image Denoising Based on Adaptive nonlinear Diffusion in Wavelet Domain
Journal of Electronic Imaging
First page number:
Last page number:
In this paper, we propose a context adaptive nonlinear diffusion method for image denoising in wavelet domain which we call context based diffusion in stationary wavelet domain (SWCD). In diffusing detail coefficients, the method adapts to the local context such that strong edges are preserved and smooth regions are diffused in a greater extent. The local context which is derived directly from the transform energies at scales 1 and 2 of two-level stationary wavelet transform (SWT) controls the diffusion. The shift invariance of SWT contributes to the performance of the method. The experiment is conducted on a number of benchmark images and compared to recently developed denoising methods which explore the adaptation concept for wavelet shrinkage and diffusion. A comparison is performed also to a method of diffusing both approximation and detail coefficients. The proposed SWCD method outperforms recently proposed adaptive shrinkage and adaptive diffusion, particularly at high noise levels. The method is computationally efficient due to the Haar wavelet and fast convergence attained due to exploiting the context information.
Electromagnetic noise; Image analysis; Image processing; Wavelets (Mathematics)
Electrical and Computer Engineering | Engineering | Signal Processing | Systems and Communications
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Mandava, A. K.,
Image Denoising Based on Adaptive nonlinear Diffusion in Wavelet Domain.
Journal of Electronic Imaging, 20(3),