Time invariant curvelet denoising
B.B. Saevarsson, Jóhannes R. Sveinsson, Jón Atli Benediktsson · 2004
The purpose of this paper is to develop a method for denoising images corrupted with additive white Gaussian noise (AWGN). The noise degrades quality of the images and makes interpretations, analysis and segmentation of images harder. In the paper the use of the time invariant discrete curvelet transform for noise reduction is considered. The discrete curvelet transform is a new image representation approach that codes image edges more efficiently than the wavelet transform. Edges are very important in image perception and with fewer coefficients to represent edges, a better denoising scheme can be achieved. By making the curvelet transform time invariant greatly reduces the energy of the error resulting in better denoising.