Edge Preserving BIT-Plane Adaptive Wiener Filter for Gaussian Noise Restoration

Abstract

Restoration of images is a significant area of research as presence of noise is unavoidable. Noises are modeled as Gaussian noise predominantly in all fields of image processing on images acquired from all spectrums. The global method of Adaptive Wiener Filter seems to perform the best amongst all the filters available. Numerous studies have established this fact. We have tried to develop a local bitplane Adaptive Wiener Filter Algorithm which performs much better than the traditional filter. The results are not only visually verifiable but the Root Mean Square Error and the Peak Signal to Noise Ratio parameters validate our results. The suggested algorithm is actually a modification of the original one hence the processing time is not significantly effected. The algorithm works because instead of the global method which blurs out the edges, the local bitplane method works on the windows in the bitplane and hence the edges are preserved in a much better way. The results are more dominant in cases with larger variance noise and larger window size which tends to get blurred more in the global method.