BACKGROUND Ischemic heart disease is one of the common fatal diseases in advanced countries. Because signal perturbation in healthy people is less than signal perturbation in patients, entropy measure can be used as an appropriate feature for ischemia detection. METHODS Four entropy-based methods comprising of using electrocardiogram (ECG) signal directly, wavelet sub-bands of ECG signals, ex...

-Based on the statistical characters of remote sensing image, this paper proposed firstly partition remote sensing image into sub-block images of suitable sizes, and then decomposing these sub-block images with biorthogonal 7/5 wavelet. A novel construction method of wavelet set of coefficients is adopted to embed binary watermarking image into sub-bands except low frequency sub-bands, and real...

Images have large data quantity, for storage and transmission of images, high efficiency image compression methods are under wide attention. In this Paper we proposed and implemented a wavelet transform and neural network model for image compression which combines the advantage of wavelet transform and neural network. Images are decomposed using Haar wavelet filters into a set of sub bands with...

Real time image processing should have high quality results at lesser computational time. A spatial image denoising method using 2D discrete wavelet transform (2D DWT) and Stationary wavelet transform (SWT) is presented in this paper for high quality image results. DWT gives high quality output at low levels of noise at relatively lesser time consumption where as it suffers from translation inv...

This paper presents a hybrid technique for compression using Wavelet and Vector Quantization (VQ). Wavelet is a technique for representing the image into various degrees of resolution. The input image of size 256 *256 pixels is divided into 4 sub-bands named LL, HL, LH, HH by applying Discrete Wavelet Transform. Vector Quantization is then applied for the lower sub band (LL). The size of lower ...

The boundary irregularity of skin lesions is of clinical significance for the early detection of malignant melanomas and to distinguish them from other lesions such as benign moles. The structural components of the contour are of particular importance. To extract the structure from the contour, wavelet decomposition was used as these components tend to locate in the lower frequency sub-bands. L...

Epilepsy is a chronic neurological disorder which is identified by successive unexpected seizures. Electroencephalogram (EEG) is the electrical signal of brain which contains valuable information about its normal or epileptic activity. In this work EEG and its frequency sub-bands have been analysed to detect epileptic seizures. A discrete wavelet transform (DWT) has been applied to decompose th...

Video magnification is a computational procedure to reveal subtle variations during video frames that are invisible to the naked eye. A new spatio-temporal method which makes use of connectivity based mapping of the wavelet sub-bands is introduced here for exaggerating of small motions during video frames. In this method, firstly the wavelet transformed frames are mapped to connectivity space a...

Wavelet based watermarking is a promising technology for embedding the information as an unperceivable signal into the digital contents. The main characteristics of wavelet are wavelets' excellent spatial localization and multi-resolution. Wavelet based modified buyer-seller watermarking protocols integrate multimedia, watermarking techniques, fingerprinting and cryptography for copyright prote...

sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. in this paper, a combination of three kinds of classifiers are proposed which classify the eeg signal into five sleep stages including awake, n-rem (non-rapid eye movement) stage 1, n-rem stage 2, n-rem stage 3 and 4 (also called slow wave sleep), and rem. twenty-five all night recordings...