• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.857-864
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• 2004

Many image compression standards such as JPEG, MPEG or H.263 are based on the discrete cosine transform (DCT) and quantization method. Quantization error. is the major source of image quality degradation. The current dequantization method assumes the uniform distribution of the DCT coefficients. Therefore the dequantization value is the center of each quantization interval. However DCT coefficients are regarded to follow Laplacian probability density function (pdf). The center value of each interval is not optimal in reducing squared error. We use mean of the quantization interval assuming Laplacian pdf, and show the effect of correction on image quality. Also, we compare existing quantization error to corrected quantization error in closed form. The effect of PSNR improvements due to the compensation to the real image is in the range of 0.2 ∼0.4 ㏈. The maximum correction value is 1.66 ㏈.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.296-303
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• 2007

Color quantization replaces the color of each pixel with the closest representative color, and thus it makes the resulting image partitioned into uniformly-colored regions. As a consequence, continuous, detailed variations of color over the corresponding regions in the original image are lost through color quantization. In this paper. we present a novel blind scheme for restoring such variations from a color-quantized input image without it priori knowledge of the quantization method. Our scheme identifies which pairs of uniformly-colored regions in the input image should have continuous variations of color in the resulting image. Then, such regions are seamlessly stitched through optimization while preserving the closest representative colors. The user can optionally indicate which regions should be separated or stitched by scribbling constraint brushes across the regions. We demonstrate the effectiveness of our approach through diverse examples, such as photographs, cartoons, and artistic illustrations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.5
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• pp.11-20
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• 2002

Based on regularization principles, we propose a new dequantization scheme on DCT-based transform coding for reducing of blocking artifacts and minimizing the quantization error. The conventional image dequantization is simply to multiply the received quantized DCT coefficients by the quantization matrix. Therefore, for each DCT coefficients, we premise that the quantization noise is as large as half quantizer step size (in DCT domain). Our approach is based on basic constraint that quantization error is bounded to ${\pm}$(quantizer spacing/2) and at least there are not high frequency components corresponding to discontinuities across block boundaries of the images. Through regularization, our proposed dequantization scheme, sharply reduces blocking artifacts in decoded images. Our proposed algorithm guarantees that the dequantization process will map the quantized DCT coefficients will be evaluated against the standard JPEG, MPEG-1 and H.263 (with Annex J deblocking filter) decoding process. The experimental results will show visual improvements as well as numerical improvements in terms of the peak-signal-to-noise ratio (PSNR) and the blockiness measure (BM) to be defined.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.880-894
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• 1997

In this paper,we propose a new algorithm to perform DCT(Discrete Cosine Transform) withn the area reduced by prdeicting position of quantization coefficients to be zero.This proposed algorithm not only decreases the enoding time and the decoding time by reducing computation amount of FDCT(Forward DCT)and IDCT(Inverse DCT) but also increases comprossion ratio by performing each diffirent horizontal- vereical zig-zag scan assording to the calssified block size for each block on the huffiman coeing.Traditional image coding method performs the samd DCT computation and zig-zag scan over all blocks,however this proposed algorthm reduces FDCT computation time by setting to zero insted of computing DCT for quantization codfficients outside classfified block size on the encoding.Also,the algorithm reduces IDCT computation the by performing IDCT for only dequantization coefficients within calssified block size on the decoding.In addition, the algorithm reduces Run-Length by carrying out horizontal-vertical zig-zag scan approriate to the slassified block chraateristics,thus providing the improverment of the compression ratio,On the on ther hand,this proposed algorithm can be applied to 16*16 block processing in which the compression ratio and the image resolution are optimal but the encoding time and the decoding time take long.Also,the algorithm can be extended to motion image coding requirng real time processing.