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The paper presents the results of modeling adaptive decomposition for ultra-high definition television, which provides image compression without subjective deterioration of quality. The decomposition of the images was carried out in the spectral region for the cases of wavelet analysis and Fourier transformation, depending on the signal-to-noise ratio at the image edges. Quantitative estimates of...
Pulsed thermography (PT) is a widely used non-destructive testing (NDT) technique for defect detection in carbon fiber reinforced polymers (CFRP) structures. Thermographic signal reconstruction (TSR) is often employed to process thermographic data due to its excellent performance in enhancing the contrast between defects and background. However, TSR does not reduce the noise of thermographic data...
Usually energy-detection based spectrum sensing techniques for Cognitive Radios need, as preliminary operation, the spectrum segmentation in smaller sub-bands, in order to apply test statistic over each sub-band rather than over the entire span, resulting in a sensitivity and selectivity improvement of the output. Despite uniform subdivision is the easiest way, the problem resides on the optimal sub-band...
This paper firstly introduces the definition and types of wavelet transform. Then we introduce the Mallat decomposition and reconstruction algorithm in detail. Secondly, after comparing the advantages and disadvantages of several Better Method, we choose wavelet thresholding and make improvements of that. At last, we compare the SNR of the signal de-noising by matlab simulation analysis to prove the...
Background: High-frequency oscillations (HFOs) are considered to be highly representative of brain tissues capable of producing epileptic seizures. The visual review of HFOs on intracerebral electroencephalography is time consuming and tedious, and it can be improved by time-frequency (TF) analysis. The main issue is that the signal is dominated by lower frequencies that mask the HFOs. Our aim was...
In order to effectively eliminate the noise in the signal, a de-noising algorithm is proposed based improved wavelet threshold algorithm. Firstly, the advantages and disadvantages of wavelet soft threshold and hard threshold method are analysis, and constructs a new threshold function with an arbitrary derivative, secondly the optimal thresholds are estimated by adjusting the parameter values, finally...
In this paper the methods of image segmentation on the base of wavelet transform and distributions is proposed. These methods improve the speed of image segmentation with a high quality under noisy conditions.
Stochastic Resonance(SR) can restore the weak signal in a strong noise background more effectively by using noise. According to this, a new way to process the noised signal in a bad noised environment has been provided. A new way of image processing based on bistable Stochastic Resonance and Wavelet transform has been given. Firstly, the noised image is processed by bistable Stochastic Resonance....
Microwave imaging represent an emerging tool in the framework of noninvasive diagnostics, due to the potential advantages of providing quantitative characterizations of the inspected domains. In general, handling such a problem is not an easy task, but under some simplifying hypotheses it is possible to reduce the ill-posedness of the inverse problem and even to employ some linearization strategies...
Computer displays emit electromagnetic waves, which compromise the information displayed by the computer. This can be a potential information security threat as the sensitive information can be stolen from a distance without leaving any trace. The video leakage signals contain the information of the image displayed in the computer, so the video leakage signals can be seen as special image signals...
There is much noise in the channel during signal transmission. The signals are easily polluted when they are transmitted in it. So they can't be received correctly. In order to get the correct signals, the polluted signals should be processed to reduce noises and improve the quality when they reach the receiver. After analyzing the theory of wavelet transform and the characteristics of traditional...
This paper suggests a novel high capacity audio watermarking technique by using the high frequency band of the wavelet decomposition, for which the human auditory system is not very sensitive to variation. The high frequency band, DD, is divided into four parts and, then, in each step, a single sample from each part is selected. The sum of the selected wavelet samples is used for embedding the secret...
This paper presents a digital audio watermarking scheme that can embed imperceptible and robust watermark image into the audio signal. The watermarking process is performed in discrete wavelet domain by applying the QR factorization on 2-D blocks of low frequency part. The watermark bits are inserted in each block by quantizing the coefficients of resulting R matrices. A particle swarm optimization...
For the problem of denoising incomplete phenomenon appeared in the existing wavelet threshold methods, a new kind of threshold function and denoising method of parameter adjustable wavelet threshold is proposed. The traditional hard threshold and soft threshold wavelet had problems such as continuity and constant deviation. Firstly, to construct a new threshold function and theoretically proves the...
Automatic modulation identification (AMI) is a significant technique to identify the modulation type of a received signal, and it is of great importance in information war and communication countermeasure. In this paper, we propose a constellation-wavelet transform automatic identifier (C-WT AMI) to identify the order of the received QAM signal. QAM is a widely used modulation type due to its high...
In this paper, the detection of shock wave that generated by supersonic bullet is considered. A wavelet based multi-scale products method has been widely used for detection. However, the performance of method decreased at low signal-to-noise ratio (SNR). It is noted that the method does not consider the distribution of the signal and noise. Thus we analyze the method under the standard likelihood...
Electrocardiogram (ECG) is a non-stationary biological signal. It detects the cardiac abnormalities by measuring the electrical activity generated in the heart. But ECG is very much sensitive. Its amplitude and duration can be corrupted by various types of noise, especially, power line interference, which sometimes leads to misdiagnosis. In this study different wavelet families identification and...
On the basis of wavelet modulus maxima characterization of local regularity theory and the advantages of wavelet transform, an optimized wavelet modulus maxima de-noising method applied on rail crack AE signal is presented in this paper. In the background of the new real-time rail crack detection method by AE, wavelet modulus maxima de-noising is proved to be an effective way to extract the crack...
An improved wavelet method is presented for TWT signal denoising, in which linear-hard and nonlinear-soft threshold regions are defined and given. In MATLAB simulation, Doppler signal affected by 7 dB of additive-white Gaussian noise is analyzed and denoised. The results show that signal to noise ratio is 24.2362 and root mean square error is 0.4356, and the improved method is better than the conventional...
Aiming at the problems in current radar signal sorting, this paper firstly analyzes the basic principle of the algorithm of the PRI transform and wavelet transform, combining the advantages and disadvantages of the two algorithms and put forward a synthetic method of radar signal sorting based on the combination of PRI transform and wavelet transform. This method firstly used PRI transform to sort...
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