• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.38-42
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• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1199-1203
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• 2012

H.264 adopted many compression tools to increase image data compression efficiency such as B frame bi-directional predictions, the direct mode coding and so on. Despite its high compression efficiency, H.264 can suffer from its long coding time due to the complicated tools of H.264. To realize a high performance H.264, several fast algorithms were proposed. One of them is adaptive fast direct mode decision algorithm using mode and Lagrangian cost prediction for B frame in H.264/AVC (MLP) algorithm which can determine the direct coding mode for macroblocks without a complex mode decision process. However, in this algorithm, macroblocks not satisfying the conditions of the MLP algorithm are required to process the complex mode decision calculation, yet suffering a long coding time. To overcome the problem, this paper proposes a fast direct mode prediction algorithm. Simulation results show that the proposed algorithm can determine the direct mode coding without a complex mode decision process for 42% more macroblocks and, this algorithm can reduce coding time by up to 23%, compared with Jin's algorithm. This enables to encode B frames fast with a less quality degradation.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2315-2318
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• 2003

The Wavelet Transform has been applied in mathematics and computer sciences. Numerous studies have proven its advantages in image processing and data compression, and have made it a basic encoding technique in data compression standards like JPEG2000 and MPEG-4. Software implementations of the Discrete Wavelet Transform (DWT) appears to be the performance bottleneck in real-time systems in terms of performance. And hardware implementations are not flexible. Therefore, FPGA implementations of the DWT has been a topic of recent research. The goal of this thesis is to investigate of FPGA implementations of the DWT Processor for image compression applications. The DWT processor design is based on the Lifting Based Wavelet Transform Scheme, which is a fast implementation of the DWT The design uses various techniques. The DWT Processor was simulated and implemented in a FLEX FPGA platform of Altera

• Journal of the Korea Society of Computer and Information
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• v.5 no.3
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• pp.64-69
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• 2000

This paper proposes a novel fractal coding method for fast encoding and high compression to shorten time to take on fractal encoding by using limited search area. First. the original image is contracted respectively by half and by quarter with the scaling method and bit-plane method. And then, the corresponding domain block of the quarter-sized image which is most similar with one range block of the half-sized image is searched within the limited area in order to reduce the encoding time extremely. As the result of the evaluation, the proposed algorithm provided much shorter encoding time and better compression ratio with a little degradation of the decoded image qualify than Jacquin's method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.11-22
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• 1997

The fractal image compression partitions an original image into blocks of equal size and searches a do-main block having self-similarity. This method of compression achieves high compression ratio because it is unnecessary to transmit the additional codebook to receiver and it provides good quality of reconstructed images. In spite of these advantages, this method has a drawback in which encoding time increase due to a complicated linear transformation for determining a similar-domain block. In this paper, a fast fractal image compression method is proposed by decreasing the number of transformation usings AC(alternating current) coefficients of block. The proposed method also has a good quality as compared with the well-known fractal codings. Furthermore, method also has a good quality as apply the video steganography that can conceal an important secret data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.521-525
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• 1998

In this paper, we propose a fast algorithm for fractal image coding to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make an image to be matched. Then, the whole area of the contracted image is searched in order to find contractive transformation point of the original image corresponding to the contacted image. It needs a lot of searching time on encoding and remains limitation in the improvement of compression ratio. However, the proposed algorithm not only considerably reduces encoding tin e by using scaling method and limited search area method but also improves compression ratio by using bit-plane. When comparing the proposed algorithm with Jacquin's method, the proposed algorithm provides much shorter encoding time and better compression ratio with a little degradation of the decoded image quality than Jacquin's method.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.246-256
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• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.121-128
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• 1994

In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5063-5073
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• 2016

In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.980-985
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• 2002

In this paper, we analyzed satellite image with a high resolution compression performance. We need much time in a fast processing on vast satellite image pixel data. On compressing and decompressing, we should keep the information about road, building, forest, etc. In conclusion, we did analyze and compare the performance of compression and decompression for JPEG and WSQ(wavelet scalar quantization) method. As a result, we knew that WSQ was more efficient than JPEG.