• ETRI Journal
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• v.27 no.6
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• pp.814-817
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• 2005

Fast binary dilation and erosion algorithms using run-length encoding (RLE) are proposed. RLE is an alternative way of representing a binary image using a run, which is a sequence of '1' pixels. First, we derive the run-based representation of dilation and erosion and then present the full steps of the proposed algorithms in detail.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.857-865
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• 1995

In this paper, a nibble RLE(Run Length Encoding) code for real time compression and decompression of Hanguel bit map font and printer data is proposed. The nibble RLE code shows good compression ratio in complete form Hangeul Myoungjo and Godik style bit map font and printer output bit map data. And two ASICs seperating compression and decompression are designed and simulated on CAD to verify the proposed code. The 0.8 micron CMOS Sea of Gate is used to implement the ASICs in amount of 2, 400 gates, and these are running at 25MHz. Therefore, the proposed code could be implemented with simple hardware and performs 100M bit/sec compression and decomression at maximum, it is good for real time applications.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.686-688
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• 2010

The supply of context information is increasing with the propagation of ubiquitous computing environment. Recently, as context information is being collected through electronic tags and sensors attached to the environment, we need methods to efficiently store and search large volumes of data. This paper describes the application of the RLE (Run Length Encoding) compression method for sensors that continuously collect data in USN/RFID terminals.Time information is marked on the data and one data block is generated and saved. This paper proposes a storage method that allows us to quickly search data of the desired time and place by recording time information in continuous data.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.49-55
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• 1999

Extracting information of maps is necessary to establish the GIS. In this paper, a house recognition method on the scanned topographic map is described. A contour detection method is used to extract houses from the scanned maps and RLE (run-length encoding) method is used for manipulating houses touching grid lines. To handle houses touched to roads and borderlines, morphological operation is used. To remove misrecognition occurred by morphological operation, the legions which contain characters on the map are also automatically eliminated.

• Journal of Information Display
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• v.10 no.1
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• pp.6-15
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• 2009

In this paper, a new approach is proposed for the efficient generation of computer-generated holograms (CGHs) using the spatially redundant data on a 3D object and the novel look-up table (N-LUT) method. First, the pre-calculated N-point principle fringe patterns (PFPs) were calculated using the 1-point PFP of the N-LUT. Second, spatially redundant data on a 3D object were extracted and re-grouped into the N-point redundancy map using the run-length encoding (RLE) method. Then CGH patterns were generated using the spatial redundancy map and the N-LUT method. Finally, the generated hologram patterns were reconstructed. In this approach, the object points that were involved in the calculation of the CGH patterns were dramatically reduced, due to which the computational speed was increased. Some experiments with a test 3D object were carried out and the results were compared with those of conventional methods.

• Journal of Astronomy and Space Sciences
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• v.13 no.2
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• pp.198-209
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• 1996

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast mount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet trans-form to remove the spatial redundancy. The transformed images are than encoded by hilbert-curve scanning and run-length-encoding, followed by huffman coding. We also present the performance of the proposed algorithm with KITSAT-1 image as well as the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by peak signal to noise ratio (PSNR) and classification capability.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.86-89
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• 2011

현재 인터넷이 생활의 일부로 자리함으로써 인터넷을 통해 수많은 멀티미디어의 교환이 발생하며, 많은 멀티미디어 서비스가 이루어지고 있다. 멀티미디어 서비스를 제공함에 있어 최근 저작권 관리 및 보호의 필요성이 대두되고 있다. 이에 따라 멀티미디어 데이터에 대한 암호기술 개발에 많은 연구가 진행되고 있으며 카오스 사상에 기반 한 암호화 연구가 최근 연구 추세이다. 본 논문은 MPEG(Moving Picture Experts Group) 인코딩 과정에서 1차원 카오스 사상(Map)을 이용하여 인트라 블록을 암호화하는 새로운 방법을 제안하고자 한다. 본 제안 시스템은 MPEG 구조 기반으로 CKD(Chaotic Key Distributor)를 이용하여 확장된 키 값으로 인트라 블록의 0이 아닌 DCT(Discrete Cosine Transform) 계수를 암호화 하는 방법이다. MPEG 인코딩 과정중 DCT 계수는 양자화를 통해 손실이 발생하더라도 비교적 많은 0값을 생성한다. 이는 RLE(Run Length Encoding) 과정에서 압축 효과를 높일 수 있다. 제안하는 방법은 영상 손실을 감수하고 수행한 양자화 과정의 효과를 유지하기 위하여 0이 아닌 DCT 계수만을 암호화 한다. 실험 결과 원본과 암호화된 MPEG의 크기의 변화는 매우 적으며, 인코딩 시간 또한 큰 차이를 보이지 않았다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.417-424
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• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.28-39
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• 2003

This paper is an overview of research contributions by the authors to the use of compression techniques to handle high resolution, multi-spectral images. Originally developed in the remote sensing context, the same techniques are here applied to food and medical images. The objective is to point out the potential of this kind of processing in different contexts such as remote sensing, food monitoring, and medical imaging and to stimulate new research exploitations. Compression is based on the simple assumption that it is possible to find out a relationship between pixels close one each other in multi-spectral images it translates to the possibility to say that there is a certain degree of correlation within pixels belonging to the same band in a close neighbourhood. Once found a correlation based on certain coefficient on one band, the coefficients of this relationship are, in turn, quite probably, similar to the ones calculated in one of the other bands. Based upon this second observation, an algorithm was developed, able to reduce the number of bit/pixel from 16 to 4 in satellite remote sensed multi-spectral images. A comparison is carried out between different methods about their speed and compression ratio. As reference it was taken the behaviour of three common algorithms, LZW (Lempel-Ziv-Welch), Huffman and RLE (Run Length Encoding), as they are used in common graphic format such as GIF, JPEG and PCX. The Presented methods have similar results in both speed and compression ratio to the commonly used programs and are to be preferred when the decompression must be carried out on line, inside a main program or when there is the need of a custom made compression algorithm.