Enhanced Wiener restoration of images based on the Haar wavelet transform

Abstract

Two proposed methods are used for enhancing the results of the linear minimum mean square error (LMMSE) or Wiener restoration. The first approach depends on adaptively merging the Wiener restoration with a regularized restoration technique, which can be solved iteratively. The second approach is a smoothing technique to reduce noise in flat areas in the, restored images. The decision that is used for selecting the regions in the image, in which either the regularization or the smoothing processes can be made, is dependent on the 2-D Haar wavelet transform.