• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.175-182
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• 2012

The scattered radiation always occurs when X-ray strikes the object. To absorb the scattered X-rays, the antiscatter grids are used, however these grids images are superimposed in the projection radiography images. When those images are displayed on the monitor, moir$\acute{e}$ patterns are overlapped over the images and disturb the anatomical informations. Most of the researches performed to date removed the grid noises by calculating or observing those frequencies in one dimensional frequency domain, two dimensional wavelet transform or Fourier transform. Those methods filtered not only the grid noises but also diagnostic informations. In this paper, we proposed the combined wavelet packet-Fourier method to remove the grid artifact in CR images. For the phantom image, the proposed method achieved from 5.2 to 7.4 dB better than others in SNR and for CR images by rejecting the grid noise bands effectively while leaving the remaining bands unchanged, the loss of images could get minimal results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.205-211
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• 2012

By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.270-277
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• 2010

The BAMS filter is a kind of wavelet shrinkage filter based on the Bayes estimators with no simulation, therefore it can be used for a real time filter. The denoising efficiency of BAMS filter is seriously affected by the estimated noise variance in each wavelet band. To remove noise in signals in existing BAMS filter, the noise variance is estimated by using the quartile of the finest level of details in the wavelet decomposition, and with this variance, the noise of the level is removed. In this paper, to remove the image noise includingodified quartile of the level of detail is proposed. And by these techniques, the image noises of mid and high frequency bands are removed, and the results showed that the increased PSNR of ab the midband noise, the noise variance estimation method using the monotonic transform and the mout 2[dB] and the effectiveness in denosing of low noise deviation images.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.45-49
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• 2013

Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.359-366
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• 2018

In this paper, the noise is removed by using CTLS aircraft installed FBG sensor inside the aircraft wing. We suggest a normal wavelet transform scheme with motion - invariant characteristics for noise reduction. In the case of installing FBG sensors inside the composite material as in CTLS, large and small empty spaces and parts or sections are generated between the adhesive layers, and a signal splitting problem occurs. FBG sensor is not affected by noise. but eletromagnetic, light source, light detector and signal processing device are influeced by noise because these are eletronic components what affected by eletromagnetic wave. because of this, errors are occured. Experimental results show that the noise can be removed using normal wavelet transform and more accurate data detection is possible.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.26-31
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• 2012

The highest frequency band of wavelet decomposition band is divided into 4 equal subbands and by the minimum power of the subbands and by the monotonic transform, the level adapted threshold is obtained. The adapted threshold is applied to the soft threshold technique to denoise high and middle frequency band noise of image signals. And the results of PSNRs are compared with the results obtained by the VisuShrink technique and by the technique using the monotonic transform and the weight value. The results showed the validity of this technique.

• Journal of Advanced Navigation Technology
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• v.20 no.3
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• pp.196-202
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• 2016

In this paper, a stationary wavelet transform method is proposed for improving the altitude control performance of quadrotor UAV using an ultrasonic rangefinder. A ground tests are conducted using an ultrasonic rangefinder that is much used for vertical takeoff and landing. An ultrasonic rangefinder suffers from signal's spike due to specular reflectance and acoustic noise. The occurred spikes in short time span need to be analyzed at both sides time and frequency domain. It was known that stationary wavelet transform is the transferring solution to the problem occurred by down sampling from DWT also more efficient to remove noise than DWT. The analyzed spikes of the ultrasonic rangefinder using a stationary wavelet transform and experimental results show that it can effectively remove the spikes of the ultrasonic rangefinder.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.10-17
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• 2008

The purpose of this thesis is to reduce of error for source location through acoustic emission(AE) signal, generated elastic wave from crack growth to leak for facility diagnosis. Especially, in order to overcome noise from original signal, this paper proposed enhancement of source location by using noise reduction based on wavelet transform. To evaluate actual performance in experiments, Pencil Lead Break is used crack signal source on the aluminum plate and drain valve of air compressor is used as substitute pressure vessel to generate leak signal. In signal processing, wavelet shrinkage and soft threshold are used to discriminate signal source and then source location techniques have been effectively used with group velocity using material property and time difference between sensor using cross correlation. Source location for crack and leak test have some difference, but the result show that improved 30% with a average length within 10.46mm in crack test and improved 2% compare with average filter in leak test when we applied wavelet transform.

• Journal of Advanced Navigation Technology
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• v.23 no.4
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• pp.273-280
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• 2019

There are many studies that use structure health monitoring to reduce maintenance costs for aircraft and to increase aircraft utilization. Many studies on FBG sensors are also being conducted. However, if the FBG sensor is installed inside the composite, voids will occur between the layers of the composite, resulting in signal split problem. In addition, the FBG sensor is not affected by electromagnetic waves, but will produce electromagnetic noise caused by electronic equipment during post-processing. In this paper, to reduce the error caused by these noises, the stationary wavelet transform, which has the characteristics of movement immutability and is efficient in nonlinear signal analysis, is presented. And in the above situation, we found that noise rejection performance of stationary wavelet transform was better compared with the wavelet packet transform.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.111-118
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• 2004

Techniques based on thresholding of wavelet coefficients are gaining popularity for denoising data because of the reasonable performance at the low complexity. The VisuShrink which removes the noise with the universal threshold is one of the techniques. The universal threshold is proportional to the noise deviation and the number of data samples. In general, because the noise deviation is not known, one needs to estimate the deviation for determining the value of the universal threshold. But, only for the finest scale wavelet coefficients, it has been known the way of estimating the noise deviation, so the noise in coarse scales cannot be removed with the VisuShrink. We propose here a new denoising method which removes the noise in each scale except the coarsest scale by Visushrink method. The noise deviation at each band is estimated by the monotonic transform and weighted deviation, the product of estimated noise deviation by the weight, is applied to the universal threshold. By making use of the universal threshold and the Soft-Threshold technique, the noise in each band is removed. The denoising characteristics of the proposed method is compared with that of the traditional VisuShrink and SureShrink method. The result showed that the proposed method is effective in denoising on Gaussian noise and quantization noise.