• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.612-613
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• 2010

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.208-213
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• 2010

Generally, the mal factor for speech recognition is the background noise in speech recognition. The noise is the reason to reduce the speech recognition performance. Owing to the fact, the place to recognize is very important. To improve the recognition performance from the sound having noise, we implemented the noise filtered Wiener filter at the signal process step which adopted the FIR filter. In FIR filter, it deal with the filtered speech signal which is appropriate frequency range of human speech frequency range. Therefore, we make the recognition system distinguish between noise and speech sound from the incoming speech signal.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2153-2158
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• 2016

Multimedia such as image, audio, and video is easy to create and distribute with the advance of IT. Since novice uses them for illegal purposes, multimedia forensics are required to protect contents and block illegal usage. This paper presents a multimedia forensic algorithm for video to identify the device used for acquiring unknown video files. First, the way to calculate a sensor pattern noise using Wiener filter (W-SPN) is presented, which comes from the imperfection of photon detectors against light. Then, the way to identify the device is explained after estimating W-SPNs from the reference device and the unknown video. For the experiment, 30 devices including DSLR, compact camera, smartphone, and camcorder are tested and analyzed quantitatively. Based on the results, the presented algorithm can achieve the 96.0% identification accuracy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.58-64
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• 2009

Digital radiography (DR) images are corrupted by the additive noise, and also distorted by system impulse response. These unwanted phenomena are obstacles to obtain the desired image. To recover the original image, we applied multiscale Wiener filters in wavelet domain for DR images. The multiscale Wiener filter is first proposed by Chen for the restoration of fractal signals which are distorted by the system impulse response and additive noise. In this paper, we extended the multiscale Wiener filter to the two dimensional data. To compare the performance of ours with others, some simulations are given for a couple of wavelet filters with different wavelet levels, system impulse reponses and various noise power. When the addive noise powers are between 20-32 dB, the signal to noise ratio(SNR) of the proposed system is 0.5-2.0 dB better than that of the traditional Wiener filter method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.113-122
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• 2016

In this paper, we suggest a approach which comprises fast Fourier transform inversion by wavelet noise attenuation. It represents an inverse filtering by adopting a factor into the Wiener filtering, and the optimal factor is chosen to minimize the overall mean squared error. in order to apply the Wiener filter, we have to compute the power spectrum of original image from the corrupted figure. Since the Wiener filtering contains the inverse filtering process, it expands the noise when the blurring filter is not invertible. To remove the large noises, the best is to remove the noise using wavelet threshold. Wavelet noise attenuation steps are consisted of inverse filtering and noise reduction by Wavelet functions. experimental results have not outperformed the other methods over the overall restoration performance.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.202-207
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• 2002

EOC (Electro-Optical Camera) of KOMPSAT-1 (Korea Multi-Purpose SATellite) has been producing land imageries of the world since January 2000. After image data are acquired by EOC, they are transmitted from satellite to ground via X-band RF signal. Then, EOC image data are generated and pass through radiometric and geometric corrections to generate standard products of EOC images. After radiometric correction on EOC image data, Modulation Transfer Function (MTF) compensation is applicable on EOC images with user's request for better image quality. MTF compensation is concerned with filtering EOC images to minimize the effect of degradations. For Image Receiving and Processing System (IRPE) at KOMPSAT Ground Station (KGS), Wiener filter is used in MTF compensation for EOC images. If the Pointing Spread Function (PSF) of EOC system is known, signal-to-noise power spectra ratio is the only factor in the determination of Wiener filter. In this paper, MTF compensation in IRPE at KGS is introduced and MTF compensated EOC 1R images are generated using Wiener filters with various signal-to-noise power spectra ratios. MTF compensated EOC 1R images are correlated with EOC 1R images for observing linearities between them. As a result, the effect of signal-to-noise power spectra ratio is shown on MTF compensated EOC 1R images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1055-1063
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• 2012

The noise of image is added by many environmental factors. Therefore, we need to remove these noises using the conventional filtering methods, which are optimized based on the statistical characteristic of noise. In direct restoration method, there is an inverse filter and the wiener filter. Here, the wiener filter is the optimized filter in the view of least square method. First, we are going to study the inverse filter, wiener filter, constraint least square filter. Second, in order to control the quantity, we use the parameters instead of the power spectrum ratio. But, these parameters have the conflicting condition, therefore, we optimized the variables using parametric wiener filter which adjust the application appropriately. In the simulation results, the contrast of the degraded image was enhanced and the noise was removed. Comparative experimentation was demonstrated edge preserving and noise removing property.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.519-524
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• 2018

Chest examinations and mass chest examinations using the CR(computed radiography) System are frequently used clinically. a factor that degrades image quality in the acquisition process is the use of unused IPs long times. this paper addresses the estimation of winer filter and improved wiener filter to restoration of Chest CR images Experimental results show that the proposed method can reduce noise. in low noise variation image wiener method was excellent than improved method and the result was the opposite at high noise varience. the application of algorithms to chest CR images effectively eliminates noise. the classic Wiener filter was better than the improved method. Multiple patients examined during the process without any erase IP(image plate) process, The proposed algorithm determines that the images can be restored to a good quality and will help to read the images.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.1005-1012
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• 1987

An adaptive scalar DCT-Wiener filtering method that can be applied to the problem of restoring an image degraded by white Gaussian noise is presented. In this method, the power spectrum needed to Winer filering is adaptively estimated in block-wise according to the lical properties in transform domain. In addition, overlapping method for reducing the block artifact is considered. Experimental results show that the adaptive Wiener filter by the proposed method yields performance improvement and better image quality over the nonadaptive one and the spatial Lee filter.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.43-46
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• 1998

Considerable research in the last three decades has examined the problem of enhancement of speech degraded by additive background noise. We compare traditional methods such as spectral subtraction and Wiener filter, recently proposed psychoacoustic model based methods such as perceptual filter and noise suppression in EVRC in terms of performance and complexity.