• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.285-294
• /
• 2004

Median Filters in the Signal Processing have been most widely used and have demonstrated the most strongest effects. This paper proposes the Adaptive Median Filters by using noise detection. The basic algorithm of the proposed filters is to determine whether noise or not by the each noise judgement standards, and then take the Median Filter if it satisfies the conditions as a result of judgement and returns to the original image(No Filters) if not. This paper presented Noise Detection by Local Variance and Local Central Variance for noise judgement, compared and analyzed the features and performance of existing [5]∼[10] Filters. Filter improved on the result of executing the existing filters at the same condition and showed the effects over that when it was judged with naked eyes. Accordingly, the Adaptive Median Filters by Local Variance and Local Central Variance was proven to have reinforced edge preservation ability and have the strong features for removing the Impulse Noise of the Median Filter.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.1
• /
• pp.13-20
• /
• 2001

Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.3
• /
• pp.517-522
• /
• 2004

In this paper, we have analyzed the performance enhancement of Orthogonal Frequency Division Multiplexing/Quadrature Phase Shift Keying Modulation-Digital Microwave Radio(OFDM/QPSK-DMR) system using Band Limited-Pulse Shaping Filter(BL-PSF) over microwave channel environments. For performance enhancement, the one-tap adaptive equalizer is adopted in the OFDM/QPSK-DMR system and than both BER and signature curve performance are compared with those of single carrier DMR system. Computer simulations confirm that the OFDM/QPSK-DMR system using 16 sub-carrier increase the fade margin about 2 dB over microwave channel environments and that of performance using one-tap adaptive equalizer is highly increased the fade margin as the number of sub-carriers is larger.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.15 no.8
• /
• pp.689-697
• /
• 1990

This paper proposes ADAPTIVE STOCHASTIC ITERATION ALGORITHM that can be used for the full-duplex digital data transmission over existing twisted-pair cables. The canceller step size changes according to the residual echo level. Thus convergence speed increases by an order of magnitude over the conventional stochastic interation alogorithm. And it can be combined with the sequential type adaptive digital filter that simplifies the conventional echo canceller circuit. Thus it is suitable for LSI implementation. Theoretical analysis on two algorithms is carried out and the algorithm simulation program is developed.

• Journal of the Korean Society for Railway
• /
• v.13 no.3
• /
• pp.283-289
• /
• 2010

Recent advance of digital camera results in that image signal processing techniques are widely adopted to railroad security management. However, due to the nature of railroad management many images are acquired in low light level environment such as night scenes. The lack of light causes lots of noise in the image, which degrades image quality and causes errors in the next processes. 3D noise reducing techniques produce better results by using consecutive sequence of images. On the other hand, they cause degradation such as motion blur if there are motions in the sequence. In this paper, we use an adaptive weight filter to estimate more accurate motions and use the result of the adaptive filter to 3D result to improve objective and subjective mage quality.

• Progress in Superconductivity
• /
• v.4 no.1
• /
• pp.53-58
• /
• 2002

Noise from electronic instrumentation is invariably present in biomedical signals, although the art of instrumentation design is such that this noise source may be negligible. And sometimes signals of interest are contaminated or degraded by signals of similar type from another source. Biomedical signals are omni-presently contaminated by these background noises that span nearly all frequency bandwidths. In the magneto-cardiogram (MCG), several digital filters have been designed for the elimination of the power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. In addition to the introduced FIR filter, notch, adaptive filter using the least mean square (LMS) algorithm, and recurrent neural network (RNN) filter, a new filtering method for effective noise canceling in MCG signals is proposed in this paper, which is realized by the wavelet packets. The experimental results show that the proposed filter using wavelet packet performs efficiently with respect to noise rejection. To verify this, two characteristics were analyzed and compared with LMS adaptive filter, SNR of filtered signal and attractor pattern using the nonlinear dynamics.

• International Journal of Computer Science & Network Security
• /
• v.22 no.11
• /
• pp.308-318
• /
• 2022

Noise is a serious issue. While sending images via electronic communication, Impulse noise, which is created by unsteady voltage, is one of the most common noises in digital communication. During the acquisition process, pictures were collected. It is possible to obtain accurate diagnosis images by removing these noises without affecting the edges and tiny features. The New Average High Noise Density Median Filter. (HNDMF) was proposed in this paper, and it operates in two steps for each pixel. Filter can decide whether the test pixels is degraded by SPN. In the first stage, a detector identifies corrupted pixels, in the second stage, an algorithm replaced by noise free processed pixel, the New average suggested Filter produced for this window. The paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. In this paper the comparison of known image denoising is discussed and a new decision based weighted median filter used to remove impulse noise. Using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structure Similarity Index Method (SSIM) metrics, the paper examines the performance of Gaussian Filter (GF), Adaptive Median Filter (AMF), and PHDNF. A detailed simulation process is performed to ensure the betterment of the presented model on the Mini-MIAS dataset. The obtained experimental values stated that the HNDMF model has reached to a better performance with the maximum picture quality. images affected by various amounts of pretend salt and paper noise, as well as speckle noise, are calculated and provided as experimental results. According to quality metrics, the HNDMF Method produces a superior result than the existing filter method. Accurately detect and replace salt and pepper noise pixel values with mean and median value in images. The proposed method is to improve the median filter with a significant change.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.99-105
• /
• 2015

This paper deals with the mMMA (modified MMA) which possible to improving the convergence speed that employing the serial connecting form of two stage digital filter instead of signal filter of MMA adaptive equalizer without applying the variable step size for compensates the intersymbol interference by channel distortion in the nonconstant modulus signal. The adaptive equalizer can be implemented by signal digital filter using the finite order tap delay line. In this paper, the equalizer is implemented by the two stage serial form and the filter coefficient are updated by the error signal using the same algorithm of MMA in each stage. The fast convergence speed is determined in the first stage, and the residual isi left at the output of first stage output is minimized in the second stage filter. The same digital filter length was considered in single stage and two stage system and the performance of these systems were compared. The performance index includes the output signal constellation, the residual isi and maximum distortion, MSE that is measure of the convergence characteristics, the SER. As a result of computer simulation, mMMA that has a FIR structure of two stage, has more good performance in every performance index except the constellation diagram due to equalization noise and improves the convergence speed about 1.5~1.8 time than the present MMA that has a FIR structure of single stage.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.19 no.2
• /
• pp.57-68
• /
• 2023

Because salt and pepper noise is a type of impulse, even a small amount of noise could cause a large image degradation. In this paper, we proposed a salt-and-pepper noise removal method using the convolutional neural network. It consists of four phases. In the first step, the proposed method reconstructs noisy image using a traditional salt-and-pepper noise reduction method, and in the second step, the result image of previous step is filtered with Gaussian low pass filter. After that, we reconstruct the filtered image using convolution neural network. In the last step, the pixels with salt-and-pepper noise are replaced with the result of previous phase. Simulation results show that the proposed method yields not only objective image qualities(PSNR, SSIM) but also subjective image qualities for all SAP noise ratios.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.500-503
• /
• 2002

Biomedical signals are ubiquitously contaminated and degraded by background noise which span nearly all frequency bandwidths. This paper proposes the MADF (multiplication free adaptive digital filter) algorithm to cancel the noise. And the convergence characteristics of the algorithm is analyzed. In the experimental results, the MADF algorithm has the advantage in which has superior to a condition of low-frequency and slow data speed. This application gives an important significance in ensuring the objectivity of clinical information and in promoting the representation and the disease diagnosis.