Year: 2022
Type: preprint
Abstract: We show how total variation regularization of images in arbitrary dimensions can be approximately performed by applying appropriate shrinkage to some Haar wavelets coefficients. The approach works directly on the wavelet coefficients and is therefore suited for the application on large volumes from computed tomography.
Source: arXiv (Cornell University)
Authors: Sauer, Tomas, Stock, A. Michael
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Award: G7784617322
OpenAlex ID: W4320520924