Topic
Discrete sine transform
About: Discrete sine transform is a research topic. Over the lifetime, 3269 publications have been published within this topic receiving 73181 citations.
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TL;DR: In this paper, a procedure for the exact interpolation of apodized, magnitude-mode Fourier transform (FT) spectra was developed for the same purpose, which is applicable for the sine-bell and Hanning windows, as well as other windows which consist of a sum of constants and sine/cosine terms.
Abstract: A procedure is developed for the exact interpolation of apodized, magnitude-mode Fourier transform (FT) spectra. The procedure gives the true center frequency, i.e., the location of the continuous peak, from just the largest three discrete intensities in the discrete magnitude spectrum. The procedure is applicable for the peaks in the apodized magnitude spectrum of time signal of the form f(t) = cos(ωt) exp(–t/τ). There are no restrictions on the value of the damping ratio T/τ. The procedure is demonstrated for the sine-bell and Hanning windows and is gener-alizable to other windows which consist of a sum of constants and sine/cosine terms. This includes the majority of commonly used windows.
13 citations
01 Aug 2019
TL;DR: In this study, compressive sampling is designed and analyzed on video watermarking and the system is resistant to Gaussian Blur and rescaling noise attacks.
Abstract: The security and confidentiality of the data can be guaranteed by using a technique called watermarking. In this study, compressive sampling is designed and analyzed on video watermarking. Before the watermark compression process was carried out, the watermark was encoding the Bose Chaudhuri Hocquenghem Code (BCH Code). After that, the watermark is processed using the Discrete Sine Transform (DST) and Discrete Wavelet Transform (DWT). The watermark insertion process to the video host using the Stationary Wavelet Transform (SWT), and Singular Value Decomposition (SVD) methods. The results of our system are obtained with the PSNR 47.269 dB, MSE 1.712, and BER 0.080. The system is resistant to Gaussian Blur and rescaling noise attacks.
13 citations
TL;DR: By making a discrete finite time signal periodic, it is shown that nonorthogonal B-spline wavelets can be used in a discrete wavelet transform with exact decomposition and reconstruction.
13 citations
TL;DR: It is shown that using cosine polynomials leads to a least squares problem involving certain Toeplitz-plus-Hankel matrices and derive estimates on the condition number of these matrices, which cannot be diagonalized by the discrete cosine transform (DCT), but they still allow a fast matrix–vector multiplication via DCT which gives rise to fast conjugate gradient type algorithms.
13 citations
TL;DR: This paper defines the time spread and the fractional frequency spread for discrete signals and derives an uncertainty relation between these two spreads, which are extended to the linear canonical transform, which is a generalized form of the FRFT.
Abstract: The fractional Fourier transform (FRFT), which generalizes the classical Fourier transform, has gained much popularity in recent years because of its applications in many areas, including optics, radar, and signal processing. There are relations between duration in time and bandwidth in fractional frequency for analog signals, which are called the uncertainty principles of the FRFT. However, these relations are only suitable for analog signals and have not been investigated in discrete signals. In practice, an analog signal is usually represented by its discrete samples. The purpose of this paper is to propose an equivalent uncertainty principle for the FRFT in discrete signals. First, we define the time spread and the fractional frequency spread for discrete signals. Then, we derive an uncertainty relation between these two spreads. The derived results are also extended to the linear canonical transform, which is a generalized form of the FRFT.
13 citations