Satellite Image Restoration by Applying the Genetic Approach to the Wiener Deconvolution

In the process of satellite imaging, the observed image is blurred by optical system and atmospheric effects and corrupted by additive noise. The image restoration method known as Wiener deconvolution intervenes to estimate from the degraded image an image as close as possible to the original image. The effectiveness of this method obviously depends on the regularization term which requires a priori knowledge of the power spectral density of the original image that is rarely, if ever, accessible, hence the estimation of approximate values can affect the restored image quality. In this paper, the idea consists of applying the genetic approach to the Wiener deconvolution for satellite image restoration through the optimization of this regularization term in order to achieve the best possible result.