The Field Programmable Gate Array (FPGA) approach is the most recent category, which takes the place in the implementation of most of the Digital Signal Processing (DSP) applications. It had proved the capability to handle such problems and supports all the necessary needs like scalability, speed, size, cost, and efficiency.

In this paper a new proposed circuit design is implemented for the evaluation of the coefficients of the two-dimensional Wavelet Transform (WT) and Wavelet Packet Transform (WPT) using FPGA is provided.

In this implementation the evaluations of the WT & WPT coefficients are depending upon filter tree decomposition using the 2-D discrete convolution algorithm. This implementation w

Accurate detection of Electro Cardio Graphic (ECG) features is an important demand for medical purposes, therefore an accurate algorithm is required to detect these features. This paper proposes an approach to classify the cardiac arrhythmia from a normal ECG signal based on wavelet decomposition and ID3 classification algorithm. First, ECG signals are denoised using the Discrete Wavelet Transform (DWT) and the second step is extract the ECG features from the processed signal. Interactive Dichotomizer 3 (ID3) algorithm is applied to classify the different arrhythmias including normal case. Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia Database is used to evaluate the ID3 algorithm. The experimental resul

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

<p>Generally, The sending process of secret information via the transmission channel or any carrier medium is not secured. For this reason, the techniques of information hiding are needed. Therefore, steganography must take place before transmission. To embed a secret message at optimal positions of the cover image under spatial domain, using the developed particle swarm optimization algorithm (Dev.-PSO) to do that purpose in this paper based on Least Significant Bits (LSB) using LSB substitution. The main aim of (Dev. -PSO) algorithm is determining an optimal paths to reach a required goals in the specified search space based on disposal of them, using (Dev.-PSO) algorithm produces the paths of a required goals with most effi

This paper is concerned with the design and implementation of an image compression method based on biorthogonal tap-9/7 discrete wavelet transform (DWT) and quadtree coding method. As a first step the color correlation is handled using YUV color representation instead of RGB. Then, the chromatic sub-bands are downsampled, and the data of each color band is transformed using wavelet transform. The produced wavelet sub-bands are quantized using hierarchal scalar quantization method. The detail quantized coefficient is coded using quadtree coding followed by Lempel-Ziv-Welch (LZW) encoding. While the approximation coefficients are coded using delta coding followed by LZW encoding. The test results indicated that the compression results are com

FG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2

      This paper introduces method of image enhancement using the combination of both wavelet and Multiwavelet transformation. New technique is proposed for image enhancement using one smoothing filter.

    A critically- Sampled Scheme of preprocessing method is used for computing the Multiwavelet.It is the 2^nd norm approximation used to speed the procedures needed for such computation.

  An improvement was achieved with the proposed method in comparison with the conventional method. 

The performance of this technique has been done by computer using Visual Baisec.6 package.

        The secure data transmission over internet is achieved using Steganography. It is the art and science of concealing information in unremarkable cover media so as not to arouse an observer’s suspicion. In this paper the color cover image is divided into equally four parts, for each part select one channel from each part( Red, or Green, or  Blue), choosing one of these channel depending on the high color ratio in that part. The chosen part is decomposing into four parts {LL, HL, LH, HH} by using discrete wavelet transform. The hiding image is divided into four part n*n then apply DCT on each part. Finally the four DCT coefficient parts embedding in four high frequency sub-bands {HH} in