• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.69-78
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• 2010

The irreversible 9/7 JPEG2000, which is one of sub-band coding techniques, has a problem of severe picture quality distortion at the edge and the background caused by the quantization error below 0.15bpp. In this paper, to solve such problems we propose a VQ(Visual Quantizer) based on L-pdf(Laplace probability density function) statistical characteristics of high frequency sub-bands. The proposed VQ is designed by visual parameter for improving the subjective quality and weighting parameter for increasing the compression ratio. A proposed method, based on 9/7 JPEG2000 scheme, gives the high subjective quality to reconstructed images below 0.15bpp and provides minimum MSE(Mean-Squared Error) regardless of the compression ratio.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.493-505
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• 1997

In this paper, a wavelet image compression method using human visually estimated quantizer is proposed. The quantizer has three components. These are constructed by using effects of frequency band, background luminance, and spatial masking. The first quantization factor is a fixed constant value for each band. The second factor is calculated by averaging four wavelet coefficients in the lowest frequency band. The third factor is determined by the difference between wavelet coefficients in the lowest frequency band. Arithmetic coding is used for encoding quantized wavelet coefficients. Coefficients in the lowest band are transmitted without loss. Therefore the compressed image is decompressed by using three quantization factors which can be calculated in the receiver. Compared with previous image compression methods which adopted human visual system, the proposed method shows improved results with less computational cost.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.25-32
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• 1997

In this paper, we propose an adaptive BTC algorithm using the characteristics of the error signals. The BTC algorithm has a avantage that it is low computational complexity, but a disadvantage that it produces the ragged edges in the reconstructed images for th esloping regions beause of coding the input with 2-level signals. Firstly, proposed methods classify the input into low, medium, and high activity blocks based on the variance of th einput. Using 1-level quantizer for low activity block, 2-level for medium, and 4-level for high, it is adaptive methods that reduce bit rates and the inherent quantization noises in the 2-level quantizer. Also, in case of processing high activity block, we propose a new quantization level allocation algorithm using the characteristics of the error signals between the original signals and the reconstructed signals used by 2-level quantizer, in oder that reduce bit rates superior to the conventional 4-level quantizer. Especially, considering the characteristics of input block, we reduce the bit rates without incurrng the visual noises.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.130-139
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• 1994

Video compression algorithms are based on removing spatial and/or temproal redundancy inherent in image sequences by predictive(DPCM) encoding, transform encoding, or a combination of predictive and transform encoding. In this paper, each 8$\times$8 DCT coefficient of DFD(displaced frame difference) is adaptively quantized by one of the four quantizers depending on total distortion level, which is determined by characteristics of HVS(human visual system) and buffer status. Therefore, the number of possible quantizer selection vectors(patterns) is 4$^{64}$. If this vectors are coded, toomany bits are required. Thus, the quantizer selection vectors are limited to 2048 for Y and 512 for each U, V by the proposed method using SWAD(sum of weighted absolute difference) for discriminating vectors. The computer simulation results, using the codebook vectors which are made by the proposed method, show that the subjective and objective image quality (PSNR) are goor with the limited bit allocation. (17Mbps)

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1180-1188
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• 2015

In this paper, we propose a new subband quantizer which is a type of quad-tree for applying to digital hologram compression based on Fresenelet transform. After executing Fresnelet transform to the captured digital holgoram, we analyze effect of the designed quantizer for the reconstructed objects from analyzing average energy of each coefficient and visual importance in all subbands. We analyze distribution of coefficient and set dynamic range for each subband, and then design subband quantizer. For enhancing effectiveness of the designed quantize, we adopt a method using the coefficients which are located out of dynamic range, which are named by exception indices. From this, we can obtain more effective quantizer which has higher performance in a range of σ′ = 5.0.

• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.23-29
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• 2002

This paper suggest the image compression that is needed to process PACS in medical information system. The image decoding method is used Linear-predictor and Lloyd-Max quantizer(quantization) in the Wavelet transform domain. Wavelet Transform Method is processed the multi-resolution by dividing image into 10 sub-bands of 3 levels. Low frequency domain that is sensitive to human visual characteristic is encoded by DPCM which is lossless encoding methods, and Lloyed-Max quantizer, the optimal quantizer for reducing ringing and aliasing in the image of inter sub-band, is used in the remaining high frequency domain of sub-band. The examination verifies that decompressed images are superior by the result that PSNR is 28.53dB on the input image, 512$\times$152 abdominal CT image and Chest image.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.221-228
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• 2005

The paper proposes the improved error diffusion halftoning system to enhance the edges using the spatial perceptual characteristics of the human visual system. The proposed method computes a spatial variation(SV), which is the difference between a pixel luminance and the average of its $3{\times}3$ neighborhood pixels' luminances weighted according to the spatial positioning. Information of edge enhancement(IEE) Is computed using the SV and the local average luminance. The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.106-113
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• 1998

Quantizer with bit rate control performs lossy compressionin moving image coding. Efficient quantizer can improve subjective quality of reconstructed image at the same bit rate because most of errors are occured at this stage. Although quantization matix of current compression stantards reflects human visual system, the performance of their quantization matrixes is not always optimal because they are not considering each image characteristics. We proposed a new adaptive optimal quantization matrix obtained by considering complexity of each image subblocks. It resulted in improvments of image quality about 0.05-0.82 dB and good subject quality at edge regions when we simulated the quantization method in various coding statndards.

• The Journal of the Acoustical Society of Korea
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• v.18 no.6
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• pp.77-83
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• 1999

H.263 is an international standard of ITU-T that can makes the service such as video phone, video conference in the transmission line less than 64Kbps. This recommendation draft has used motion estimation/compensation, transform coding and quantizing methods. TMN5 used for the performance estimation of H.263 has fundamentally used DCT in transform coding method and presented quantizer for quantizing the DCT transform coefficient. This paper is presenting adaptive quantizer effectively able to quantize DCT coefficient considering the human visual sensitivity while the structure of TMN5 is maintaining. As quantizer that proposed DCT-based H.263 could make transmit more frame than TMN5 in a same transfer speed, it could lower the frame drop effect. And the luminance signal appeared the difference of -0.3 ～ +0.7dB in the average PSNR for the estimation of objective image quality and the chrominance signal appeared the improvement in about 1.5dB in comparision with TMN5. As a result it can attain the better image quality compared to TMN5 in the estimation of subjective image quality.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.195-200
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• 2008

To compress the moving picture data effectively, it is needed to reduce spatial and temporal redundancy of input image data. While motion estimation! compensation methods is effectively able to reduce temporal redundancy but it is increased computation complexity because of the prediction between frames. So, the study of algorithm for computation reduction and real time processing is needed. This paper is presenting quantizer effectively able to quantize DCT coefficient considering the human visual sensitivity. As quantizer that proposed DCT-based H.263 could make transmit more frame than TMN5 at a same transfer speed, and it could decrease the frame drop effect. And the luminance signal appeared the difference of $-0.3{\sim}+0.65dB$ in the average PSNR for the estimation of objective image quality and the chrominance signal appeared the improvement in about 1.73dB in comparision with TMN5. The proposed method reduces $30{\sim}31%$ compared with NTSS and $20{\sim}21%$ compared to 4SS in comparition of calculation quantity.