HYBRID IMAGE DENOISING USING WIENER FILTER WITH DISCRETE WAVELET TRANSFORM AND FRAMELET TRANSFORM

Abstract

Removal of noise from an image is an essential part of image processing systems. In this paper a hybrid denoising algorithm which combines spatial domain Wiener filter and thresholding function in the wavelet and framelet domain is done. In this work three algorithms are proposed. The first hybrid denoising algorithm using Wiener filter with 2-level discrete wavelet transform (DWT), the second algorithm its using Wiener filter with 2-level framelet transform (FLT) and the third hybrid denoising algorithm its combines wiener filter with 1-level wavelet transform then apply framelet transform on LL of wavelet transform. The Wiener filter is applied on the low frequency subband of the decomposed noisy image. This stage will tend to cancel or at least attenuate any residual low frequency noise component. Then thresholding detail high frequency subbands using thresholding function. This approach can be used for grayscale and color images. The simulation results show that the performance of the first proposed hybrid denoising algorithm with discrete wavelet transform (db5 type) is superior to that of the second and third proposed algorithms and to that of the conventional denoising approach at most of the test noisy image with Gaussian noise and Slat & pepper noise while the third proposed denoising algorithm with hybrid wavelet & framelet transform is superior to that of the other proposed algorithms at noisy images with speckle noise.