Study of the Principal Component Analysis Method for the Correction of Images Degraded by Turbulence
Résumé
This article analyzes and discusses a well-known paper [D. Li, R.M. Mersereau and S. Simske,
IEEE Letters on Geoscience and Remote Sensing, 3:4 (2007), pp. 340–344] that applies principal
component analysis in order to restore image sequences degraded by atmospheric turbulence.
We propose a variant of this method and its ANSI C implementation. The proposed variant
applies to image sequences acquired with short as well as long exposure times. Examples of
restored images using sequences of real atmospheric turbulence are presented. The acquisition
of a dataset of image sequences with real atmospheric turbulence is described and the dataset
is made available for download.