Image restoration by applying the genetic approach to the iterative Wiener filter

Abstract

The image restoration method entitled Wiener de-convolution intervenes to improve the quality of images subjected to the degradation effects of both blur and noise. The effectiveness whose this method has demonstrated in this kind of situations, obviously depends on the regularization term that has a direct impact on the expected result. This regularization term requires a priori knowledge of the power spectral density of the original image that is rarely accessible, hence the estimation of approximate values can affect the image quality. An amelioration has been brought to this method, which consists to iterate the Wiener filter to estimate the power spectral density of the original image. The optimization of the iteration count of the iterative Wiener filter by genetic approach leads to the better result.