• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.1-7
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• 2002

This paper proposes a algebraic parameter determination of MRA(Model Reference Adaptive Control) controller using block Pulse functions and block Pulse function's differential operation. Generally, adaption is performed by solving differential equations which describe adaptive low for updating controller parameter. The proposes algorithm transforms differential equations into algebraic equation, which can be solved much more easily inn a recursive manner. We believe that proposes methods are very attractive and proper for parameter estimation of MRAC controller on account of its simplicity and computational convergence.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.12-14
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• 2005

In this paper, we proposed an temporal error concealment (EC) using the proposed boundary matching method and the adaptive block matching method. The proposed boundary matching method improves the spatial correlation of the macroblocks (MBs) by reusing the pixels of the concealed MB to estimate a motion vector of a error MB. The adaptive block matching method inspects the horizontal edge and the vertical edge feature of a error MB surroundings, and it conceals the error MBs in reference to more stronger edge feature. This improves video quality by raising edge connection feature of the error MBs and the neighborhood MBs. In particular, we restore a lost MB as the unit of 8${\times}$16 block or 16${\times}$8 block by using edge feature from the surrounding macroblocks. Experimental results show that the proposed algorithm gives better results than the conventional algorithms from a subjective and an objective viewpoint.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.785-790
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• 2019

In this paper, a new bilateral frame rate up-conversion algorithm using adaptive overlapped block motion compensation is proposed. In this algorithm, the adaptive overlapped block motion compensation is based on the motion complexity of the reference region. As the motion complexity is determined by the size of the previously coded motion estimation prediction, the overlapped block motion compensation method is selected without any additional computational complexity. Experimental results show that the proposed algorithm provides better image quality than conventional methods both objectively and subjectively.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.8-14
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• 2001

In this paper, we present a new cost function for subband block adaptive algorithm and block conjugate gradient algorithm for noise cancellation of acoustic signal. For the cost function, we process the subband signals with data blocks for each subbands and recombine it a whole data block. After these process, the cost function has a quadratic form in adaptive filter coefficients, it guarantees the convergence of the suggested block conjugate gradient algorithm. And the block conjugate gradient algorithm which minimizes the suggested cost function has better performance than the case of full-band block conjugate gradient algorithm, the computer simulation results of noise cancellation show the efficiency of the suggested algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.2
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• pp.187-196
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• 2017

The size of raw data has dramatically increased due to the recent trend of Synthetic Aperture Radar(SAR) development plans for high resolution and high definition image acquisition. The large raw data has an impact on satellite operability due to the limitations of storage and transmission capacity. To improve the SAR operability, the SAR raw data shall be compressed before transmission to the ground station. The Block Adaptive Quantization (BAQ) algorithm is one of the data compression algorithm and has been used for a long time in the spaceborne SAR system. In this paper, an optimization method of BAQ threshold table is introduced using real SAR raw data to prevent the degradation of signal quality caused by data compression. In this manner, a new variation estimation strategy and a new threshold method for block type decision are introduced.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.44-47
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• 1991

There exists a transform trellis code that is optimal for stationary Gaussian sources and the squared-error distortion measure at all rates. In this paper, we train an asymptotically optimal version of such a code to obtain one which is matched better to the statistics of real world data. The training algorithm uses the M-algorithm to search the trellis codebook and the LBG-algorithm to update the trellis codebook. To adapt the codebook for the varying input data. we use two gain-adaptive methods. The gain-adaptive scheme 1, which normalizes input block data by its gain factor, is applied to images at rate 0.5 bits/pixel. When each block is encoded at the same rate, the nonstationarity among the block variances leads to a variation in the resulting distortion from one block to another. To alleviate the non-uniformity among the encoded image, we design four clusters from the block power, in which each cluster has its own trellis codebook and different rates. The rate of each cluster is assigned through requiring a constant distortion per-letter. This gain-adaptive scheme 2 produces good visual and measurable quality at low rates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.455-461
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• 2011

In object tracking using the block mating algorithm, it is not proper to use a fixed matching block to track an object of which size may be various and can be changed at any time. This paper defines an adaptive matching block for the dynamic environment and proposes a block matching algorithm for it. The matching block is composed of a main-block of $10{\times}10$ pixels and 8 sub-blocks of $6{\times}6$ pixels in a wide area of $42{\times}42$ pixels, the main-block located its center is used as an object block, and the sub-blocks located its boundary are used as candidates for the object block. The proposed algorithm extracts the object blocks from the sub-blocks by using their motion vectors for 10 previous frames and performs the block matching with the main block and them. The experiments for perform estimation show that the proposed algorithm extracts just valid object blocks from the matching block and keeps an object having free movement in image center area.