• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.1
• /
• pp.11-21
• /
• 2008

In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.12
• /
• pp.2798-2804
• /
• 2010

The audio and image signal are corrupted by various noises in signal processing, many studies are being accomplished to restore those signals. In this paper, the algorithm is proposed to remove additive Gaussian noise and impulse noise at one dimension signal like an speech signal. The algorithm is composed to remove Gaussian noise after removing impulse noise. And the method using wavelet coefficient accumulation is used to remove the Gaussian noise, and the median filter based on element deviation is applied to remove the impulse noise. Also we compare existing methods using SNR(signal-to-noise ratio) as the standard of judgement of improvemental effect.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.10
• /
• pp.2447-2453
• /
• 2013

The digital images are being degraded by noise in the process of acquisition, storage and transmission, Gaussian or impulse noise is the representative noise. Meanwhile, the image has lots of tendency to be degraded by complex noise, so various researches are being conducted for reducing these complex noise. In this paper, to remove complex noise, the algorithm processed by modified switching median filter and modified adaptive weighted filter according to the result after judging the kinds of noise is proposed. In the simulation result, excellent denoising capabilities. Furthermore, we compared proposed algorithm with existing methods for objective judgement, and PSNR(peak signal to noise ratio) is used by the criterion of judgement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.671-673
• /
• 2016

In image data, noise occurs due to various external factors in the process of obtaining and transmitting. There are various types of noise according to the cause and form and research to remove this noise is being continued. Therefore the study suggested a way to filter to restore images damaged by salt and pepper noise which preserves non-noise signal and processes noise signal by expanding mask size according to the local mask noise density. In addition, as an objective evaluation standard of improvements, the study used PSNR(peak signal to noise ratio) to compare with previous methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.214-216
• /
• 2019

Recently, as the use of digital equipment increases in various fields, the importance of image and signal processing is increasing. However, many kinds of noise occur in the digital signal during transmission and reception, and this noise greatly affects the final output of the system. In this paper, we propose an algorithm that effectively restores the image by removing noise according to pixel similarity in a mixed noise environment with impulse noise and AWGN. The proposed algorithm sets the reference value according to the noise type and applies the filtering to pixels similar to the reference value to obtain the final output. Simulation results show that the proposed algorithm has good noise canceling performance and compared with conventional methods using PSNR.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.89-92
• /
• 1999

인식기 훈련과정에서 발생하지 않았던 잡음이 인식과정에서 신호를 손상할 경우 인식률의 저하가 발생한다. 본 논문에서는 음성의 질을 떨어뜨리는 이러한 잡음을 Wavelet Packets을 이용하여 전처리함으로서 인식률을 향상시키는 방법을 제안한다. 인식기로는 Hidden Markov Model을 사용하였고, 시스템에 사용된 특징 파라미터로는 15차 Cepstrum을 사용하였다. 11 kHz로 샘플링된 숫자음에 Additive White Gaussian Noise를 첨가한 손상된 음성신호를 인식실험에 사용하였다. 화자독립으로 진행된 실험에서 잡음에 의해 손상된 SNR 20dB의 음성신호에 대하여 Wavelet Packets로 잡음을 제거한 후 복원된 음성신호 의 인식률은 약 $10\%$ 향상됨을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.8
• /
• pp.1094-1101
• /
• 1993

We show that image compression possibilities of BDPCM which reduces information and increases correlation with signal-blurring. Under the same quantization steps, signal flow at the coder is analyzed and complete signal reconstruction properties are shown. Dynamic range characteristics of the differences by the conventional DPCM predictor are analyzed. In order to improve the median filter reduces impulse noise with blurring, adaptive filtering for the differences is proposed. By means of the difference range, transmission impulse noises are detected and corrected by the filtering. Therefore, low bit rate image codec with noise eliminations is proposed.

• Korean Journal of Optics and Photonics
• /
• v.25 no.3
• /
• pp.142-145
• /
• 2014

In this paper we record the complex hologram of a real object with optical scanning holography (OSH). We reconstruct the complex hologram using a numerical process, and then we evaluate the degree of contamination by speckle noise between the reconstruction of the complex hologram and the image captured by a CCD camera. We use the contrast of the speckle pattern for quantitative evaluation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.254-257
• /
• 2010

본 논문에서는 신경회로망을 사용하여 이산푸리에변환에 의한 진폭성분과 위상성분을 복원하는 음성강조 시스템을 제안한다. 본 시스템은 신경회로망이 잡음이 부가된 음성신호의 이산푸리에변환의 진폭성분과 위상성분을 사용하여 학습된 후, 제안한 시스템은 배경잡음에 의하여 열화된 잡음이 부가된 음성신호를 강조한다. 배경잡음에 의하여 열화된 음성신호는 신경회로망을 사용하여 제안된 시스템에 의하여 강조되는 것을 실험결과로 증명하며, 제안한 시스템이 스펙트럼 왜곡율의 평가법을 사용하여 배경잡음에 의하여 열화된 음성신호에 대하여 효과적인 것을 실험으로 확인한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.341-344
• /
• 2009

본 논문에서는 신경회로망(Neural network)에 시간구조를 도입한 시간지연 신경회로망(Time-delay Neural Network: TDNN)을 사용하여 잡음을 포함한 음성신호로부터 잡음을 제거함으로써 음성을 강조하는 것을 목적으로 한다. 본 논문에서는 먼저 각 프레임의 FFT 진폭성분들을 유성음 구간과 무성음 구간으로 검출한 후, 무성음 구간에 대해서는 각 프레임에서 이동평균을 취하여 음성을 강조한다. 유성음 구간에 대해서는 각 프레임의 FFT 진폭성분들을 저역, 중역 및 고역으로 각각 분리한 후에 각 대역의 FFT 진폭성분들을 저역용 TDNN, 중역용 TDNN, 그리고 고역용 TDNN의 입력으로 하여 각 TDNN에 학습시킴으로써 최종 FFT 진폭성분들을 구한다. 본 실험에서는 Aurora2 데이터베이스를 사용하여 FFT의 진폭성분을 복원하는 잡음제거의 알고리즘을 사용하여 여러 잡음에 대해서 본 알고리즘의 유효성을 실험적으로 확인한다.