Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This research presents discrete M-band wavelet transform (DMWT) and cosine transform (DCT) based watermarking algorithm by incorporating the randomization and principal component analysis (PCA). The proposed algorithm is expected to ...

Determining depth of anesthesia is a challenging problem in the context of biomedical signal processing. Various methods have been suggested to determine a quantitative index as depth of anesthesia, but most of these methods suffer from high sensitivity during the surgery. A novel method based on energy scattering of samples in the wavelet domain is suggested to represent the basic content of e...

A wavelet-based method is introduced in this paper for efficient speckle suppression and detection of calculi in sonographic images of the kidney.Wavelets are developed in applied mathematics for the analysis of multiscale image structures. The aim of this project is to analyse and to provide most significant content descriptive parameters to identify and classify the kidney stones with ultraso...

In this paper a high payload lossless digital image watermarking technique based on Integer Wavelet Transform is proposed. Digital watermarking is the process of embedding the watermark image into a host image which is imperceptible by human visual system. The small deviations in data values are not allowed in certain images for obvious reasons and a potential risk of a person misinterpreting a...

The objective is to develop a non-invasive automatic method for detection of epileptic seizures with motor manifestations. Ten healthy subjects who simulated seizures and one patient participated in the study. Surface electromyography (sEMG) and motion sensor features were extracted as energy measures of reconstructed sub-bands from the discrete wavelet transformation (DWT) and the wavelet pack...

Resolution and contrast are the two important attributes of an image. In this paper we developed a method to enhance the quality of the given image. The enhancement is done both with respect to resolution and contrast. The proposed technique uses DWT and SVD. To increase the resolution, the proposed method uses DWT and SWT. These transforms decompose the given image into four sub-bands, out of ...

An improved architecture for two-dimensional discrete wavelet transform (2D-DWT) to implement bi-orthogonal CohenDaubechies-Feuvear (CDF) (2,2) wavelet with line-based method is proposed for FPGA implementation using lifting scheme. The FPGA based hardware implementation profits especially from the high parallelism in the architecture and the moderate number precision required to preserve the q...

In this work, we have documented and compare various feature extraction methods for classification using EEG signal. This paper contains a comparative study of data reduction methods which enhances the classification accuracy. Deep study of decomposition of signals into the frequency sub bands by wavelet method (DWT) and a set of statistical features that were extracted from the EEG signals to ...

The image forgery detection technology based on non sampling wavelet transform coupling with Zernike moments is proposed in this article. Specifically, LL and HH sub-bands are obtained through non sampling wavelet transform to calculate the similarity and the diversity of the image blocks, and then LL similarity and HH diversity are combined for dual judgment. Meanwhile, Zernike moments are int...

A major step toward the use of hyperspectral sensors to detect subpixel targets is the ability to detect constituent absorption bands within a pixel’s hyperspectral curve. This paper introduces the use of multiresolution analysis, specifically wavelet transforms, for the automated detection of low amplitude and overlapping constituent bands in hyperspectral curves. The wavelet approach is evalu...