Department of Mathematics
Fast minimization methods for solving constrained total-variation superresolution image reconstruction
In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient. © 2010 Springer Science+Business Media, LLC.
Alternating direction methods, Constrained total-variation, Inexact computation, Superresolution image reconstruction
Source Publication Title
Multidimensional Systems and Signal Processing
Link to Publisher's Edition
Ng, M., Wang, F., & Yuan, X. (2011). Fast minimization methods for solving constrained total-variation superresolution image reconstruction. Multidimensional Systems and Signal Processing, 22 (3-1), 259-286. https://doi.org/10.1007/s11045-010-0137-9