With progress in radar systems, a number of methods have been developed for signal processing and detection in radars. A number of modern radar signal processing methods use time-frequency transforms, especially the wavelet transform (WT) which is a well-known linear transform. The interference canceling is one of the most important applications of the wavelet transform. In Ad-hoc detection met...

introduction: wavelet transform is one of the useful and suitable tools for time series and signal analysis. nowadays wavelet transform is frequently used in geophysical data processing and interpretation, especially seismic data. however, the use of this method isn’t widespread in gravity and geomagnetic. fedi and quarta (1998), martelet et al. (2001) and de oliveira lyrio (2004) used the wave...

Recently, there has been a considerable attention given to the motion detection problem due to the explosive growth of its applications in video analysis and surveillance systems. While the previous approaches can produce good results, an accurate detection of motion remains a challenging task due to the difficulties raised by illumination variations, occlusion, camouflage, burst physical motio...

More and more computer vision systems take part in the automation of various applications. The main task of such systems is to automate the process of visual recognition and to extract relevant information from the images or image sequences acquired or produced by such applications. One essential and critical component in almost every computer vision system is image segmentation. The quality of...

spectral decomposition is a powerful tool for analysis of seismic data. fourier transform determines the frequency contents of a signal. but for analysis of non-stationary signals, 1-d transform to frequency domain is not sufficient. in early years, transforming of seismic traces into time and frequency domain was done via windowed fourier transform, called a short time fourier transform (stft)...

The Multi-scale Variance Stabilization Transform (MSVST) has recently been proposed for 2D Poisson data denoising. In this work, we present an extension of the MSVST with the wavelet transform to multivariate data–each pixel is vector-valued–, where the vector field dimension may be the wavelength, the energy, or the time. Such data can be viewed naively as 3D data where the third dimension may...

in this paper a wavelet-based logo watermarking scheme is presented. the logo watermark is embedded into all sub-blocks of the lln sub-band of the transformed host image, using quantization technique. extracted logos from all sub-blocks are merged to make the extracted watermark from distorted watermarked image. knowing the quantization step-size, dimensions of logo and the level of wavelet tra...

ABSTRACT The wavelet scattering transform (WST) has recently gained attention in the context of large-scale structure studies, being a possible generator summary statistics encapsulating non-Gaussianities beyond reach conventional power spectrum. This work examines three-dimensional solid harmonic WST line-intensity mapping measurement to be undertaken by current and proposed phases CO Mapping ...