• ETRI Journal
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• v.4 no.3
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• pp.18-29
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• 1982

In a block adaptive filtering procedure, the filter coefficients are adjusted once per each output block while maintaining performance comparable to that of widely used LMS adaptive filtering in which the filter coefficients are adjusted once per each output data sample. An efficient implementation of block adaptive filter is possible by means of discrete transform technique which has cyclic convolution property and fast algorithms. In this paper, the block adaptive filtering using Fermat Number Transform (FNT) is investigated to exploit the computational efficiency and less quantization effect on the performance compared with finite precision FFT realization. And this has been verified by computer simulation for several applications including adaptive channel equalizer and system identification.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1435-1438
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• 2005

In hands-free telephone systems, the received speech signal is fed back to the microphone and constitutes the so-called echo. To cancel the effect of this time-varying echo path, it is necessary to device an adaptive filter between the receiving and the transmitting ends. For a typical FIR realization, the length of the fullband adaptive filter results in high computational complexity and low convergence rate. Consequently, subband adaptive filtering schemes have been proposed to improve the performance. In this work, we use deterministic approach to analyze the relationship between fullband and subband adaptive filtering structures. With block adaptive filtering structure as an intermediate stage, the analysis is divided into two parts. First, to avoid aliasing, it is found that the matrix of block adaptive filters is in the form of pseudocirculant, and the elements of this matrix are the polyphase components of the fullband adaptive filter. Second, to transmit the near-end voice signal faithfully, the analysis and the synthesis filter banks in the subband adaptive filtering structure must form a perfect reconstruction pair. Using polyphase representation, the relationship between the block and the subband adaptive filters is derived.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.66-69
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• 2000

In this paper, we proposed a postprocessing algorithm for quantization effects reduction in block coded images using the block classification and adaptive filtering. The proposed method consists of classification, adaptive inter-block filtering, and intra-block filtering. First, each block is classified into one of seven classes based on the characteristics of 8${\times}$8 DCT coefficients. Then each block boundary is filtered by adaptive inter-block filters according to the block classification. Finally for blocks which are classified into edge block, intra-block filtering is peformed. Experimental results show that the proposed method gives better results than the conventional methods from both a subjective and an objective viewpoint.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.706-713
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• 1997

In this paper, we propose a band stop filter(BSF) for reducing drag-like effect of the low pass filter(LPF), a block by block adaptive filtering method, and a motion adaptive filtering method, which show better results in terms of PSNR or human visual perception compared to the conventional method using LPF. The BSF improves the draglike effects of the low pass filter by passing temporal high frequency components of video sequences which correspond to objects with large motion. The proposed adaptive methods also improve the conventional adaptive filtering by modifying the conventional algorithm and applying the algorithms for small blocks. The simulation results show that the proposed filtering methods show better results in terms of PSNR and subjective tests in most cases. Also in case of block by block adaptive filtering, it is verified that the application of the algorithm for smaller block gives better results.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1269-1271
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• 2009

We had proposed fast thermal stress estimation methodology for the components on system board when the system is stationary within specific ambient air temperature. Now, we will propose one efficient thermal stress estimation methodology, block adaptive filtering methodology, for the FPD electronic system board which is enclosed by mechanical cover.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6A
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• pp.592-601
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• 2002

A postprocessing method for blocking artifact reduction in block coded images is presented. The proposed method consists of classification, adaptive inter-block filtering, and intra-block filtering. First, each block is classified as one of seven classes according to the characteristics of 8x8 DCT coefficients. Then each block boundary is faltered by adaptive inter-block filters, which use the block classes. Finally to the blocks which are classified as edge block classes, intra-block filtering is performed. Experimental tests produced that the proposed method gives better results than the convectional methods from both a subjective and an objective viewpoint.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.442-452
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• 2001

In this paper, we proposed a postprocessing algorithm for quantization effects reduction in block coded images using the block classification and adaptive filtering. The proposed method consists of classification, adaptive inter-block filtering, and intra-block filtering. First, each block is classified into one of seven classes based on the characteristics of 8$\times$8 DCT coefficients. Then each block boundary is filtered by adaptive inter-block fitters according to the block classification. finally for blocks which are classified into edge block, intra-block filtering is performed. Experimental results show that the proposed method gives better results than the conventional methods from both a subjective and an objective viewpoint.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1474-1482
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• 2004

In this paper, we propose an approach for extracting and filtering block motion vectors using an adaptive weight function. We first extract motion vectors from a sequence of images by using size-varibale block matching and then process them by adaptive robust estimation to filter out outliers (motion vectors out of concern). The proposed adaptive robust estimation defines a continuous sigmoid weight function. It then adaptively tunes the sigmoid function to its hard-limit as the residual errors between the model and input data are decreased, so that we can effectively separate non-outliers (motion vectors of concern) from outliers with the finally tuned hard-limit of the weight function. The experimental results show that the suggested approach is very effective in filtering block motion vectors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.6
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• pp.308-316
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• 1985

A new implementation of Block Adaptive filter in frequency domain is presented in this paper. Block digital filtering involves the calculation of a block or finite set of filter out put from a block of input values. A fast convergence algorithm of block adaptive filter is developed using Gordar theory and compared with the performance results of Satio algorithm and BLMS algorithm. Form the result we can be shown that the convergence state of given algorithm is not only faster than BLMS algorithm but also the resulting convergence error is less than the convergence error of Satio algorithm.