Adaptive Wiener Filter Based on Fast Lifting Wavelet Transform for Image Enhancement

A lifting-based wavelet domain Wiener filter (LBWDMF) in image enhancement is proposed. Lifting schemes have emerged as a powerful method for implementing bi-orthogonal wavelet filters. The method transforms an image into the wavelet domain using lifting-based wavelet filters and then applies a Wiener filter in the wavelet domain and finally transforms the result into the spatial domain. LBWDMF not only helps in reducing the number of computations but also achieves lossy to lossless performance with finite precision. The proposed method utilizes the multi-scale characteristics of the wavelet transform and the local statistics of each sub-band. In order to validate the effectiveness of the proposed method the result obtained using the proposed method show that the method has better performance in terms of PSNR.