Sharif Digital Repository

Adaptive filtering has been used for speech denoising in the time domain. During the last decade, wavelet transform has been developed for speech enhancement. In this paper we are proposing to use adaptive filtering in the Wavelet transform domain. We propose a hybrid method of using adaptive filters on the lower scales of a wavelet transformed speech together with the conventional methods (Thresholding, Spectral Subtraction, and Wiener filtering) on the higher scale coefficients. Experimental results demonstrate that the suggested approach is computationally efficient and has a good performance. © 2005 IEEE  

A new robust image adaptive digital watermarking algorithm in wavelet transform domain is proposed in this paper. The proposed method exploits Human Visual System (HVS) characteristics and entropy masking concept to determine image adaptive thresholds for selection of perceptually significant coefficients. The mark is embedded in the coefficients of all subbands including the LL subband. Experimental results show that the proposed method significantly improves watermarking performance over conventional methods, in the terms of invisibility and robustness  

This paper presents a new algorithm for detecting user-selected objects in a sequence of images based on a new weighted adaptive lifting scheme transform. In our algorithm, we first select a set of coefficients as object features in the wavelet transform domain and then build an adaptive transform considering the selected features. The goal of the designed adaptive transform is to "vanish" the selected features as much as possible in the transform domain. After applying both non-adaptive and adaptive transforms to a given test image, the corresponding transform domain coefficients are compared for detecting the object of interest. We have verified our claim with experimental results on 1-D...