• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.587-599
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• 1996

In general fractal imge compression, each range block is approximated by a contractive transform of the matching domain block under the mean squared error criterion. In this paper, a distortion measure reflecting the properties of human visual system is defined and applied to a fractal image compression. the perceptual distortion measure is obtained by multiplying the mean square error and the noise sensitivity modeled by using the background brightness and spatial masking. In order to compare the performance of the mean squared error and perceptual distortion measure, a simulation is carried out by using the 512*512 Lena and papper gray image. Compared to the results, 6%-10% compression ratio improvements under improvements under the same image quality are achieved in the perceptual distortion measure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.45-55
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• 1993

In this paper, a two-stage block matching algorithm (BMA), which can reduce greatly the computational complexity of the conventional BMAs, is proposed, in which the onedimensional distortion measure based on the integral projection is introduced to determine the candidate motion vectors and then among them a final motion vector is detected based on the conventional two-dimensional distortion measure. Due to the one-dimensional calculation of a distortion measure, the proposed algorithm can reduce the computational complexity of the conventional BMA (full search method with a 16$\times$16 block) by a factor of 4, with its performance comparable to those of the conventional ones. Simulation results based on the original and noisy image sequences are shown. Also the simulation of the proposed method combined with the MPEG (Moving Picture Experts Group) SM3 (Simulation Model Three) is presented. Computer simulation shows that the proposed algorithm is fast with its performance comparable to those of the conventional ones.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.931-936
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• 2006

This paper presents different issues of the real-time compression algorithms without compromising the video quality in the distributed environment. The theme of this research is to manage the critical processing stages (speed, information lost, redundancy, distortion) having better encoded ratio, without the fluctuation of quantization scale by using IP configuration. In this paper, different techniques such as distortion measure with searching method cover the block phenomenon with motion estimation process while passing technique and floating measurement is configured by discrete cosine transform (DCT) to reduce computational complexity which is implemented in this video codec. While delay of bits in encoded buffer side especially in real-time state is being controlled to produce the video with high quality and maintenance a low buffering delay. Our results show the performance accuracy gain with better achievement in all the above processes in an encouraging mode.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.848-854
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• 1996

Many image display devices allow only a limited number of colors to be simultaneously displayed. in disphaying of natural color image using color palette, it is necessary to construct an optimal color palette and the optimal mapping of each pixed of the original image to a color from the palette. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. The same as the clustering process, original color value. The proposed algorithm incroporated with a spatial activity weighting value which is reflected sensitivity of HVS quantization errors in smoothing region. This method produces high quality display images and considerably reduces computation time.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.57-62
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• 1994

The demand of image compression is increasing now for the integration of medical images into the hospital information system. Even though the quantitative distortion can be measured from the difference between original and reconstructed images, it doesn't include the nonlinear characteristics of human visual system. In this study, we have evaluated the nonlinear characteristics of human visual system and applied them to the compression of medical images. The distortion measures which reflect the characteristics of human visual system has been considered. This image compression procedure consists of coding scheme using JND (Just Noticeable Difference) curve, polynomial approximation and BTC (Block Truncation Coding). Results show that this method can be applied to CT images, scanned film images and other kinds of medical images with the compression ratio of 5-10:1 without any noticeable distortion.

• 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 Biomedical Engineering Research
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• v.15 no.1
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• pp.83-88
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• 1994

The transform trellis code is an optimal source code as a block size and the constraint length of a shift register go to infinite for stationary Gaussian sources with the squared-error distortion measure. However to implement this code, we have to choose the finite block size and constraint length. Moreover real-world sources are inherently non stationary. To overcome these difficulties, we developed a training algorithm for the transform trellis code. The trained transform trellis code which uses the same rates to each block led to a variation in the resulting distortion from one block to another. To alleviate this non-uniformity in the encoded image, we constructed clusters from the variance of the training data and assigned different rates for each cluster.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.79-85
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• 2010

In video standards such as H.264/AVC, motion estimation (ME) / compensation (MC) is regarded as a vital component in a video coder as it consumes a large amount of computation resources. The full search technique, which is used in general video codecs, gives the highest visual quality but also has the problem of significant computational load. To solve this problem, many fast algorithm has benn proposed. Among them, NPDS show that can maintain its video quality very close to the full search technique while achieving computation reduction by using a halfway-stop technique in the calculation of block distortion measure. In this paper, we proposed algorithm by determining minimum distortion measure with predictive motion vector and using the new search order. As the result, we can check that the proposed algorithm reduces the computational load 95% in average compared to the full search, respectively with the PSNR lost about 0.04dB.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.867-869
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• 2012

FRUC(Frame Rate Up Conversion) is core techniques for higher quality terminals or low channel rate. For these applications, in this paper, we propose a block-based reliability evaluation method for FRUC techniques using bi-lateral symmetrical motion estimation. First, in order to measure the reliability, by introducing cost evaluation tools such as motion vector consistency as well as temporal matching and spatial matching characteristics and then by combining these tools, we propose an efficient method which arrange the blocks according to distortion size. Through several simulations, it is shown that the proposed method is very effective in finding the high distortion blocks. Furthermore, it is expected that the proposed method can be effectively utilized in FRUC techniques and Distributed Video Coding technologies.