Sharif Digital Repository

An improved compression algorithm for ECG signals is presented using temporal alignment of beats and 2-D wavelet packet transform (WPT). This 2-D transform based approach utilizes the fact that the electrocardiogram (ECG) signals generally show two types of correlation, namely correlation between subsequent samples within each ECG cycle (intrabeat) and correlation between subsequent cycles (interbeat). One simple compression algorithm in the 2-D WPT domain, which is applied to some records in the MIT-BIH arrhythmia database shows lower percent root mean square difference (PRD) than 1-D wavelet based compression methods for the same compression ratio (CR). © 2001 IEEE  

The Wavelet based speech enhancement is considered. In this method, the noisy signal transfers to wavelet domain. Then with applying a thresholding algorithm, the wavelet coefficients will be improved. At last using the inverse wavelet transform the enhanced signal will be obtained. In this paper, we have presented a new method for thresholding algorithm. We compared our algorithm with some of the most popular methods by several experimental tests. Both subjective and objective tests show better performance and achievements  

This paper describes a new real-time algorithm for tracking user-selected objects in a sequence of images based on a new block matching algorithm in wavelet domain. In our algorithm, the amplitude of coefficients in the best basis tree expansion of un-decimated wavelet packet transform is; used as the feature vectors (FVs). Real-time object tracking have been achieved using a new search technique for finding the best match among FVs of the reference block and FVs of the search area in the wavelet domain. Our experimental results show that the algorithm is robust to various object deformations and noisy video sequences  

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further... 

The authors address the use of sparse representation to securely hide a message within non-overlapping blocks of a given colour image in the wavelet domain. All four sub-images of the two-dimensional wavelet transform of two colour bands are used for data embedding without affecting the image perceptibility. Bit error rate of hidden data extraction is reduced to zero by introducing a novel refinement procedure in the proposed algorithm. The refinement procedure introduced solves the hidden bit extraction errors caused by the rounding process, the overflows and the nature of approximation in sparse decomposition. Capacity of the proposed method is calculated using necessary conditions for... 

A new high capacity method for transform domain image steganography is introduced in this paper. The proposed steganography algorithm works on the wavelet transform coefficients of the original image to embed the secret data. As compared to current transform domain data hiding methods, this scheme can provide a larger capacity for data hiding without sacrificing the cover image quality. This is achieved through retaining integrity of the wavelet coefficients at high capacity embedding. This improvement to capacity-quality trading-off interrelation is analyzed in detailed and experimentally illustrated in the paper  

When performing segmentation using tree based representations it is evident that contiguous objects are often dispersed widely across the tree making controlled selection difficult. This paper demonstrates robust segmentation by the generation of Binary Partition Trees entirely within the wavelet domain. By using spatial frequency in conjunction with colour, a threshold free tree is produced which compels objects to reside inside single branches of the tree by constraining their merging development. Experimental results show the superior performance of the proposed algorithm compared to the existing colour based BPT algorithms. ©2008 IEEE  

This paper presents a lossless data hiding method using coefficients of integer wavelet domain. The modification of selected small coefficients of the high frequency subbands are used to embed data. We use the histogram modification to intelligently select the proper coefficients for data hiding. Data embedding is done by processing these selected coefficients. We show that at low payload data hiding our method has comparable PSNR than the best known reversible data hiding techniques, while at higher payloads it has significant superiority on image quality. ©2007 IEEE  

Along with the improvement of image watermarking techniques, the necessity for effectively and comprehensively evaluating various algorithms becomes imperative. In this paper, we first propose a new categorization that fits for most of the existing watermarking algorithms that work in the wavelet domain. Then an adaptive watermarking attack for evaluating the robustness of watermarking schemes that are based on the proposed categorization is presented. This attack determines the flat regions, edges, and textures of the watermarked image and based on known features of each region the proposed attack tries to destroy the watermark information. This is done by separately manipulating the... 

Due to the large volume required for medical images for transmission and archiving purposes, the compression of medical images is known as one of the main concepts of medical image processing. Lossless compression methods have the drawback of a low compression ratio. In contrast, lossy methods have a higher compression ratio and suffer from lower quality of the reconstructed images in the receiver. Recently, some selective compression methods have been proposed in which the main image is divided into two separate regions: Region of Interest (ROI), which should be compressed in a lossless manner, and Region of Background (ROB), which is compressed in a lossy manner with a lower quality. In... 

In this paper, we proposed a categorization for most of the existing watermarking algorithms that work in wavelet domain. Then an adaptive watermarking attack for digital images that is based on the proposed categorization is presented. This attack determines the flat regions, edges and textures of the watermarked image and based on known features of each region the proposed attack tries to destroy the watermark information by manipulating the wavelet coefficients of each region separately such that the least visual distortion will be imposed on the attacked image. We have tested the proposed method to attack two recent and robust watermarking methods and the results sound impressive. The... 

A Multiplicative Patchwork Method (MPM) for audio watermarking is proposed in this paper. In order to embed watermark data within the host signal, two subsets of the host signal features are selected using two secret keys. Then, watermark data is inserted simply by multiplying one subset and leaving the other one unchanged. In order to have an error free detection in attack-free case, embedding is performed in the selected frames of the host signal which satisfies a certain condition. This method is implemented in the wavelet domain and approximation coefficients are used for data embedding. Furthermore, the inaudibility of watermark insertion is controlled using iterative approach aided by... 

This paper presents a Multiplicative Patchwork Method (MPM) for audio watermarking. The watermark signal is embedded by selecting two subsets of the host signal features and modifying one subset multiplicatively regarding the watermark data, whereas another subset is left unchanged. The method is implemented in wavelet domain and approximation coefficients are used to embed data. In order to have an error-free detection, the watermark data is inserted only in the frames where the ratio of the energy of subsets is between two predefined values. Also in order to control the inaudibility of watermark insertion, we use an iterative algorithm to reach a desired quality for the watermarked audio... 

One of the most important parameters in evaluating a watermarking algorithm is its capacity. In fact, capacity has a paradoxical relation with other two important parameters: image quality and robustness. Some works have been done on watermarking capacity and a few on image complexities. Most works on watermarking capacity is based on information theory and the capacity values which are calculated based on these methods are very tolerate. In this paper we propose a new method for calculating image complexity based on Region Of Interest (ROI) concept. After that we analyze three complexity measures named: Image compositional complexity (ICC), Quad tree and ROI method, with three different... 

In this paper, our main purpose is to embed data in the frequency domain of audio signals. Data was embedded by means of Quantization Index Modulation (QIM) in the frequency domain. With this aim, the spectrum of the audio signal was divided into two parts. The first part consisted of the first 19 Barks and the second included the remaining 6 Barks. Each of these parts had a different quantization step size. In order to have large quantization step sizes which yield more robustness, Human Auditory System (HAS) has been used. Decoder detects the watermark signal, without using the original audio signal. Simulation results have shown that this watermarking scheme has better robustness against... 

This paper introduces a quantization noise robust algorithm for object's shape prediction in a video sequence. The algorithm is based on pixel representation in the undecimated wavelet domain for tracking of the user-defined shapes contaminated by the compression noise of video sequences. In the proposed algorithm, the amplitude of coefficients in the best basis tree expansion of the undecimated wavelet packet transform is used as feature vectors (FVs). FVs robustness against quantization noise has been achieved through inherent denoising and edge component separation in the best basis selection algorithm. The algorithm uses these FVs to track the pixels of small square blocks located at the...