• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2261-2268
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• 2010

The information captured by imaging devices such as CCD or CIS may contain external noises through the processes of passing signals or storing images. In this paper, we propose a Modified Sigma Filter (MSF) algorithm to reduce such noises. In experiment, we verified that our MSF algorithm showed better performance in PSNR and 1D plot of simulation results compared with Gaussian Filter (GF), Local Sigma Filter (LSF). Tested images include random Gaussian Noises.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.151-156
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• 2010

This paper is a study on image noise reduction of modified sigma filter by image decomposition using directivity. Conventional sigma filter has been shown to be a good solution both in terms of filtering accuracy and computational complexity. However, the sigma filter does not preserve well small edges especially for high level of additive noise. In this paper, we propose here a new method using a modified sigma filter. In our proposed method the input image is first decomposed in two components that have features of horizontal, vertical and diagonal direction. Then, two components are applied HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Added noise is removed and our proposed method preserves the edges from the image. Comparative results from experiments show that the proposed algorithm achieves higher gains, on average, 2.6 dB PSNR than the sigma filter and 0.5 dB PSNR than the modified sigma filter. When relatively high levels of noise added, the proposed algorithm shows better performance than two conventional filters.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.3-5
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• 2007

This paper presents decision feedback equalizers using a recurrent neural network trained algorithm using extended Kalman filter(EKF) and sigma-point Kalman filter(SPKF). EKF is propagated, analytically through the first-order linearization of the nonlinear system. This can introduce large errors in the true posterior mean and covariance of the Gaussian random variable. The SPKF addresses this problem by using a deterministic sampling approach. The features of the proposed recurrent neural equalizer And we investigate the bit error rate(BER) between EKF and SPKF.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2649-2655
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• 2015

While the oversampling sigma-delta ADCs are known to have high resolution, they often suffer from SNDR losses when operated at a very high data clock. This paper presents a design and implementation of a decimation filter that provides minimum distortion at passband for high-speed sigma-delta ADC. The proposed digital decimation filter employs a butterworth structure. To evaluate the performance of the proposed decimation filter, we implemented a 1-bit, third-order, OSR=64 sigma-delta modulator followed by the proposed decimation filter. Using the simulation ad measurement, we compared the performance of the proposed decimation filter with a conventional CIC(cascaded integrator comb) decimation filter, which is commonly used in most sigma-delta ADCs. The measurement results show that the proposed decimation filter presents substantially lower distortion at passband and thus can provide must higher SNDR.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.141-148
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• 2012

A design of a 32-bit fourth-stage decimation filter decimation filter used in sigma-delta analog-to-digital (A/D) converter is proposed in this work. A four-stage decimation filter with down-sampling factor of 512 and 32-bit output is developed. A multi-stage cascaded integrator-comb (CIC) filter, which reduces the sampling rate by 64, is used in the first stage. Three half-band FIR filters are used after the CIC filter, each of which reduces the sampling rate by two. The pipeline structure is applied in the CIC filter to reduce the power consumption of the CIC. The Canonic Signed Digit (CSD) arithmetic is used to optimize the multiplier structure of the FIR filter. This filter is implemented based on a semi-custom design flow and a 130nm CMOS standard cell library. This decimation filter operates at 98.304 MHz and provides 32-bit output data at an audio frequency of 192 kHz with power consumption of $697{\mu}W$. In comparison to the previous work, this design shows a higher performance in resolution, operation frequency and decimation factor with lower power consumption and small logic utilization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.405-408
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• 2015

While the oversampling sigma-delta ADCs are known to have high resolution, they often suffer from SNDR losses when operated at a very high data clock. This paper presents a design and implementation of a decimation filter that provides minimum distortion at passband for high-speed sigma-delta ADC. The proposed digital decimation filter employs a butterworth structure, which is a type of an IIR filter. To evaluate the performance of the proposed decimation filter, we implemented a 1-bit, third-order, OSR=64 sigma-delta modulator followed by the proposed decimation filter. Using the simulation ad measurement, we compared the performance of the proposed decimation filter with a conventional CIC(cascaded integrator comb) decimation filter, which is commonly used in most sigma-delta ADCs. The measurement results show that the proposed decimation filter presents substantially lower distortion at passband and thus can provide must higher SNDR.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.3
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• pp.322-326
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• 1988

The sigma filter is a nonlinear filter of modifying average filter to develop edge-preserving characteristics. However, this filter is yet weak to the impulsive noise such as BSC noise. Therefore it has not been used so highly in the image restoration area. In this paper, We propose an adaptive image restoration algorithm using the local statistic and the characteristic of human eyes in order to compensate its drawback and to improve its performance. The performance of the proposed algorithm and the vonventional ones are compared for images degraded by BSC noise. The proposed algorithm shows better performance than the median filter and yields 5 dB performance improvement over the convertional K-sigma filter on SNR gain.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.19-26
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• 2007

In the sigma filter, there is a specialized neighbours distribution scheme in which the sigma value is computed from local statistics. It is designed to modify a standard average filter to preserve edges. However this filter is vulnerable to details-enhancement and conventional sigma approaches have been focused on denoising, not enhancing the characteristic area. This paper proposes an adaptive image enhancement algorithm using local statistics and functional synthesis which are utilized for adaptive realization of the enhancement, so that not only image noise may be smoothed but also details may be enhanced. For the local adaptation, parameters are estimated and weighted at each moving window that satisfy the criteria. The experimental results illuminates the effectiveness of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.189-196
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• 2010

In this paper, we proposed the adaptive local sigma filter reducing noises generated by an image sensor. The small noises generated by the image sensor are amplified by increased an analog gain and an exposure time of the image sensor together with information. And the goal of this work was the system design that is reduce the these amplified noises. Edge data are extracted by Flatness Index Map algorithm. We made the threshold adaptively changeable by the luminance average in this algorithm that extracts the edge data not in high luminance, but just low luminance. The Local Sigma Filter performed only about the edge pixel that were extracted by Flatness Index Map algorithm. To verify the performance of the designed filter, we made the Window test program. The hardware was designed with HDL language. We verified the hardware performance of Local Sigma Filter system using FPGA Demonstration board and HD image sensor, $1280{\times}720$ image size and 30 frames per second.

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.4
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• pp.233-239
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• 2009

A mixed CT/DT 2-1 cascaded ${\Sigma\Delta}M$ which includes a first stage CT ${\Sigma\Delta}M$ and a second stage mismatch insensitive two-channel time-interleaved DT ${\Sigma\Delta}M$ is proposed. With this approach, the advantages of both CT and DT ${\Sigma\Delta}Ms$ including high speed operation, inherent anti-aliasing filter, and good coefficient matching can be achieved. The two-channel time-interleaved ${\Sigma\Delta}M$ used in the second stage alleviates the speed constraints of the DT ${\Sigma\Delta}M$, whereas enables better matching between the analog and digital filter coefficients compared to CT ${\Sigma\Delta}Ms$.