Physical-based optimization for non-physical image dehazing methods

Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied. Some of the most successful image dehazing algorithms are based on image processing methods but do not follow any physical image formation model, which limits their performance. In this paper, we propose a post-processing technique to alleviate this handicap by enforcing the original method to be consistent with a popular physical model for image formation under haze. Our results improve upon those of the original methods qualitatively and according to several metrics, and they have also been validated via psychophysical experiments. These results are particularly striking in terms of avoiding over-saturation and reducing color artifacts, which are the most common shortcomings faced by image dehazing methods.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:28

Enthalten in:

Optics express - 28(2020), 7 vom: 30. März, Seite 9327-9339

Sprache:

Englisch

Beteiligte Personen:

Vazquez-Corral, Javier [VerfasserIn]
Finlayson, Graham D [VerfasserIn]
Bertalmío, Marcelo [VerfasserIn]

Links:

Volltext

Themen:

Journal Article

Anmerkungen:

Date Revised 31.03.2020

published: Print

Citation Status PubMed-not-MEDLINE

doi:

10.1364/OE.383799

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM308112296