Spatial image denoising in Discrete Wavelet Transform domain

The uniform wavelet thresholding is one of the most widely used methods for image denoising in the Discrete Wavelet Transform (DWT) domain. This method, however, has the drawback of blurring the edges and the textures of an image after denoising. A new algorithm is proposed in this paper for image denoising in the DWT domain with no blurring effect. This algorithm uses a suite of feature extraction and image segmentation techniques to construct filter masks for denoising. The novelty of the algorithm is that it directly extracts the edges and texture details of an image from the spatial information contained in the LL subband of DWT domain rather than detecting the edges across multiple scales. An added advantage of this method is the substantial reduction in computational complexity. Experimental results indicate that the new algorithm would yield higher quality images(both qualitatively and quantitatively) than the existing methods.