3D Adaptive Wavelet Shrinkage Denoising while Preserving Fine Structures
By this contribution we tackle the challenge of denoising MRI image data while preserving fine structures. Log-Gabor wavelets offer a good compromise between spatial and spectral resolution, thus allowing to extract the local phase at all image voxels. Shrinking only the complex-valued wavelet response vectors at different scales and orientations leaves the essential phase information undistorted. We propose an adaptive shrinking threshold based on supervoxels and also based on the amount of texture in a particular image region. Therefore, the proposed adaptive 3D technique preserves fine structures and outperforms existing methods in terms of peak signal-to-noise ratio (PSNR)/structural similarity (SSIM) in cases of elevated noise perturbation.
Unable to display preview. Download preview PDF.
- 1.Saha PK, Udupa JK. Scale-based diffusive image filtering preserving boundary sharpness and fine structures. IEEE Trans Biomed Eng. 2001;20(11):1140–1155.Google Scholar
- 2.Kovesi P. Phase preserving denoising of images. Austr Pat Recogn Soc Conf DICTA. 1999;4(3):212–217.Google Scholar
- 3.Canny J. A computational approach to edge detection. IEEE Trans Pattern Anal Mach Intell. 1986;(6):679–698.Google Scholar
- 4.Achanta R, Shaji A, Smith K, et al. SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell. 2012;34(11):2274–2282.Google Scholar
- 5.Morariu CA, Dohle DS, Tsagakis K, et al. Extraction of the aortic dissection membrane via spectral phase information. In: proc BVM. Springer; 2015. p. 305–310.Google Scholar