• Journal of Korea Society of Digital Industry and Information Management
• /
• v.11 no.1
• /
• pp.171-182
• /
• 2015

The general wavelet transform has profitable property in non-stationary signal analysis specially. The tunable Q-factor wavelet transform is a fully-discrete wavelet transform for which the Q-factor Q and the asymptotic redundancy r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The transform is based on a real valued scaling factor and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its over-sampling rate, with modest over-sampling rates being sufficient for the analysis/synthesis functions to be well localized. This paper describes filter design of 2D discrete-time wavelet transform for which the Q-factor is easily specified. With the advantage of this transform, perfect reconstruction filter design and implementation for performance improvement are focused in this paper. Hence, the 2D transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. Therefore, application for performance improvement in multimedia communication field was evaluated.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.5
• /
• pp.390-395
• /
• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

• Korean Journal of Mathematics
• /
• v.23 no.1
• /
• pp.129-151
• /
• 2015

In this paper, we prove an $L^p$ version of Donoho-Stark's uncertainty principle for the inverse of the hypergeometric Fourier transform on $\mathbb{R}^d$. Next, using the ultracontractive properties of the semigroups generated by the Heckman-Opdam Laplacian operator, we obtain an $L^p$ Heisenberg-Pauli-Weyl uncertainty principle for the inverse of the hypergeometric Fourier transform on $\mathbb{R}^d$.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.5
• /
• pp.66-79
• /
• 2009

In this paper, we propose a new adaptive intra coding technique using 1-D and 2-D integer transforms for improving coding efficiency of H.264/AVC. Proposed technique selects the most effective transform and prediction mode for each block after processing 1-D and 2-D transforms of all prediction modes. In case of using 1-D transform, $4{\times}4$ block is divided into four $1{\times}4$ or $4{\times}1$ subblocks and then each subblock is predicted and subtracted by using the decoded subblock located at the nearest position in the direction of prediction. After prediction error subblock is processed by 1-D transform and quantization, four subblocks are merged back into original $4{\times}4$ block and then, reordered as 1-D signal by a DC biased zigzag scanning pattern according to the prediction mode. Finally, comparing the coding efficiency between bitstreams based on 1-D transform and conventional 2-D transform, prediction mode and quantized coefficients for each block are decided and corresponding quantized coefficients are transmitted. Experimental results show that the proposed adaptive technique increases 0.34dB in BD-PSNR and decreases 4.03% in BD-Bitrate on the average compared with H.264/AVC.

• Journal of Electrical Engineering and information Science
• /
• v.1 no.1
• /
• pp.160-163
• /
• 1996

New formulas for McClellan transform parameters for the design of 2-D zero-phase FIR fan filters are optimally derived under the integral squared error(ISE) criterion. By imposing the constraint that F(0, 0)=\ulcorner, where F($.$) is the McClellan transform and $\omega$\ulcorner is the cutoff frequency of the 1-D prototype filter, the ISE is directly minimized without modifying it and, as a consequence, closed-form formulas for the McClellan transform parameters are obtained. It is shown that these formulas lead to a very efficient design for 2-D zero-phase FIR fan filters.

• Proceedings of the IEEK Conference
• /
• 2000.06c
• /
• pp.23-26
• /
• 2000

In this paper, to perform iris recognition, the iris is changed to 1-D iris signature and methods of efficient iris pattern transformation are discussed. To represent iris signature's frequency characteristics, Fourier transform, Gabor filtering, and wavelet transform are proposed. The consistency between same person's iris and the discrimination between different person's iris are defined by using correlation. Based on these, three transform methods are compared and analyzed.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.50 no.6
• /
• pp.272-282
• /
• 2001

This paper developed improved fast Walsh transform based on dyadic-ordered fast Walsh transform, then regenerated signal flow graph of improved fast Walsh transform, and used it for digital filtering, and then measured fundamental frequency and harmonics for current and voltage signals of power system. Using the improved fast Walsh transform, we present a new algorithm which reduces the computational amount, and it can consequently calculate the real and imaginary components for current and voltage signals of power system in sampling intervals. The calculation amount is reduced to 2(N-1) at N samples to measure full harmonics using developed algorithm. When, in single harmonic measuring, it needs only 2(log2N-1) additions and subtractions.

• KIEE International Transactions on Power Engineering
• /
• v.11A no.4
• /
• pp.1-8
• /
• 2001

This paper presents a discrete wavelet transform approach for detecting voltage sags initialized by fault conditions and starting of larger motors. The proposed technique is based on utilizing the summation value of D1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. In this paper, the proposed technique is tested under various cases of voltage sags. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• Journal of the Institute of Convergence Signal Processing
• /
• v.11 no.1
• /
• pp.1-8
• /
• 2010

Noise removal methods for noisy images have been studied a lot in the domain of spatial and transform filtering. Low pass filtering was initially applied in the spatial domain. Recently, discrete wavelet transform has widely used for image denoising as well as image compression due to an excellent energy compaction and a property of multiresolution. In this paper, Gabor cosine and sine transform which is considered as human visual filter is applied to image denoising areas using soft thresholding technique. GCST is compared with excellent wavelet transform which uses existing soft thresholding methods from PSNR point of view. Resultant images removed noises are also visually compared. Experimental results with adding four different standard deviation levels of Gaussian distributed noises to real images show that the proposed transform has better PSNR performance of a maximum of 1.18 dB and visible perception than wavelet transform.

• Nonlinear Functional Analysis and Applications
• /
• v.26 no.1
• /
• pp.105-115
• /
• 2021

Generalized pseudo-differential operators (PDO) involving fractional Fourier transform associate with the symbol a(x, y) whose derivatives satisfy certain growth condition is defined. The product of two generalized pseudo-differential operators is shown to be a generalized pseudo-differential operator.