• 한국통신학회논문지
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• 제25권6B호
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• pp.1028-1040
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• 2000

Since image data has large data amount, proper image compression is necessary to transmit and store the data efficiently. Image compression brings about bit rate reduction but results in some artifacts. This artifacts are blocking artifacts, mosquito noise, which are observed in DCT based compression image, and ringing artifacts, which is perceived around the edges in wavelet based compression image. In this paper, we propose directional postprocessing technique which improved the decoded image quality using the fact that human vision is sensible to ringing artifacts around the edges of image. First we detect the edge direction in each block. Next we perform directional postprocessing according to detected edge direction. Proposed method is that the edge direction is block. Next performed directional postprocessing according to detected edge direction. If the correlation coefficients are equivalent to each directions, postprocessing is not performed. So, time of the postproces ing brings about shorten.

• 대한전자공학회논문지SD
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• 제48권4호
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• pp.51-56
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• 2011

본 논문에서는 CAN 버스로드를 줄여 CAN 네트워크 비용을 줄이고 오류 확률을 낮추기 위해서 메시지를 압축하는 방법을 제안한다. 제안하는 비트 재배열 방법은 기존의 메시지 변화량만 전송하는 압축방식과 달리 각 변화량의 하위 비트들로부터 시작하여 전송데이터를 재구성하도록 하여 결과적으로 데이터가 압축되는 방법이다. 차량 CAN 로깅 파일을 이용하여 제안한 방법으로 압축한 결과 전송 데이터량이 기존 압축알고리즘에 비해 26% 더 감소함을 보였다.

• Current Optics and Photonics
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• 제3권5호
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• pp.390-400
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• 2019

Encrypted images obtained through double random phase-encoding (DRPE) occupy considerable storage space. We propose efficient compression schemes to reduce the size of the encrypted data. In the proposed schemes, two state-of-art compression methods of JPEG and JP2K are applied to the quantized encrypted phase images obtained by combining the DRPE algorithm with the virtual photon counting imaging technique. We compute the nonlinear cross-correlation between the registered reference images and the compressed input images to verify the performance of the compression of double random phase-encoded images. We show quantitatively through experiments that considerable compression of the encrypted image data can be achieved while security and authentication factors are completely preserved.

• 한국인터넷방송통신학회논문지
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• 제8권6호
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• pp.49-54
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• 2008

최근에 무선 통신 기술 및 지리정보시스템(GIS)의 발달과 더불어 모바일 GIS에 대한 관심이 높아지고 있다. 이러한 모바일 GIS는 기존의 서버 컴퓨팅 환경과는 다르게 자원이 매우 제한적인 모바일 환경에 최적화되어야 한다. 특히, 모바일 GIS에서는 대용량 공간 데이터를 모바일 장치에 적합하게 줄이는 것이 매우 중요하다. 그러나 기존의 공간 데이터 압축 기법은 데이터를 가변적으로 처리하는 기법으로써 데이터의 크기를 예측하기가 매우 힘들며, 순차적으로 처리해야만 하는 단점이 존재한다. 따라서, 본 논문에서는 모바일 GIS를 위한 셀기반 공간 데이터 압축 기법을 제시한다. 본 논문에서 제시하는 셀기반 공간 데이터 압축 기법은 모바일 환경에서 클라이언트로 공간 데이터를 제공할 때 셀 단위로 전송하는 것을 기반으로 하여 압축하는 방법이다. 마지막으로, 본 논문에서는 실제 데이터를 통한 성능 평가를 수행함으로써 셀기반 공간 데이터 압축 기법의 우수성을 입증하였다.

• 한국도로학회논문집
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• 제17권6호
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• pp.27-32
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• 2015

PURPOSES : It is difficult to estimate tunnel stability because of lack of timely information during tunnel excavation. Tunnel deformability refers to the capacity of rock to strain under applied loads or unloads during tunnel excavation. This study was conducted to analyze a methods of pre-evaluation of stability during tunnel construction using the critical strain concept, which is applied to the results of tunnel settlement data and unconfined compression strength of intact rock or rock mass at the tunnel construction site. METHODS : Based on the critical strain concept, the pre-evaluation of stability of a tunnel was performed in the Daegu region, at a tunnel through andesite and granite rock. The critical strain concept is a method of predicting tunnel behavior from tunnel crown settlement data using the critical strain chart that is obtained from the relationship between strain and the unconfined compression strength of intact rock in a laboratory. RESULTS : In a pre-evaluation of stability of a tunnel, only actually measured crown settlement data is plotted on the lower position of the critical strain chart, to be compared with the total displacement of crown settlement, including precedent settlement and displacement data from before the settlement measurement. However, both cases show almost the same tunnel behavior. In an evaluation using rock mass instead of intact rock, the data for the rock mass strength is plotted on the lower portion of the critical strain chart, as a way to compare to the data for intact rock strength. CONCLUSIONS : From the results of the pre-evaluation of stability of the tunnel using the critical strain chart, we reaffirmed that it is possible to promptly evaluate the stability of a tunnel under construction. Moreover, this research shows that a safety evaluation using the actual instrumented crown settlement data with the unconfined compression strength of intact rock, rather than with the unconfined compression strength of a rock mass in the tunnel working face, is more conservative.

• International Journal of Contents
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• 제11권2호
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• pp.31-36
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• 2015

Recent years have seen a significant increase in demand for multimedia data over wireless sensor networks for monitoring applications that utilize sensor nodes to collect multimedia data, including sound and video. However, the multimedia streams generate a very large amount of data. When data transmission schemes for traditional wireless sensor networks are applied in wireless multimedia sensor networks, the network lifetime significantly decreases due to the excessive energy consumption of specific nodes. In this paper, we propose a data compression scheme that implements the Chinese remainder theorem to a wireless multimedia sensor network. The proposed scheme uses the Chinese Remainder Theorem (CRT) to compress and split multimedia data, and it then transmits the bit-pattern packets of the remainder to the base station. As a result, the amount of multimedia data that is transmitted is reduced. The superiority of our proposed scheme is demonstrated by comparing its performance to that of an existing scheme. The results of our experiment indicate that our proposed scheme significantly increased the compression ratio and reduced the compression operation in comparison to those of existing compression schemes.

• Journal of Computing Science and Engineering
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• 제10권1호
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2485-2489
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• 2005

This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.358-360
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• 2004

The digital images contain a significant amount of redundancy and require a large amount of data for their storage and transmission. Therefore, the image compression is necessary to treat digital images efficiently. The goal of image compression is to reduce the number of bits required for their representation. The image compression can reduce the size of image data using contractive mapping of original image. Among the compression methods, the mapping is affine transformation to find the block(called range block) which is the most similar to the original image. In this paper, we applied the neural network(SOM) in encoding. In order to improve the performance of image compression, we intend to reduce the similarities and unnecesaries comparing with the originals in the codebook. In standard image coding, the affine transform is performed with eight isometries that used to approximate domain blocks to range blocks.

• 한국멀티미디어학회논문지
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• 제7권12호
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.