A dynamical analysis on non-local autoregressive model and its application on image reconstruction

Dong Sun, Fangfang Li, Qingwei Gao and Yixiang Lu

Chaos, Solitons & Fractals, 2020, vol. 130, issue C

Abstract: Natural images are highly structured, which reflects strong spatial redundancy underlying its pixels. In this paper, a dynamical analysis of the non-local autoregressive (NAR) model is researched for the first time. We prove that under the condition when the spectrum radius of NAR matrix is less than 1, the original image as the global stable fixed point of function system referring to a modified NAR model can be iteratively recovered via attractor reconstruction from an arbitrary start point.

Keywords: Non-local autoregressive model; Iterated function system; Attractor; Spectrum radius; Image reconstruction (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077919303674
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:130:y:2020:i:c:s0960077919303674

DOI: 10.1016/j.chaos.2019.109427

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().