• Journal of KIISE:Databases
• /
• v.30 no.6
• /
• pp.553-560
• /
• 2003

A range-sum query is very popular and becomes important in finding trends and in discovering relationships between attributes in diverse database applications. It sums over the selected cells of an OLAP data cube where target cells are decided by specified query ranges. The direct method to access the data cube itself forces too many cells to be accessed, therefore it incurs severe overheads. The prefix-sum cube was proposed for the efficient processing of range-sum queries in OLAP environments. However, the prefix-sum cube has been criticized due to its space requirement. In this paper, we propose a lossless compression method called the overlapped-subcube that is developed for the purpose of compressing prefix-sum cubes. A distinguished feature of the overlapped-subcube is that searches can be done without decompressing. The overlapped-subcube reduces the space requirement for storing prefix-sum cubes, and improves the query performance.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.5
• /
• pp.33-41
• /
• 2011

In this paper, we propose a lossless compression scheme for cloud point data of the target construction by using doubleness and decreasing useless information of cloud point data. We use Hough transform to find the horizontal angle between construction and terrestrial LIDAR. This angle is used for the rotation of the cloud point data. The cloud point data can be parallel to x-axis, then y-axis doubleness is increased. Therefore, the cloud point data can be more compressed. In addition, we apply two methods to decrease the number of cloud point data for useless information of them. One is decimation of the cloud point data, the other is to extract the range of y-coordinates of target construction, and then extract the cloud point data existing in the range only. The experimental result shows the performance of proposed scheme. To compress the data, we use only the position information without additional information. Therefore, this scheme can increase processing speed of the compression algorithm.

• Journal of Korea Multimedia Society
• /
• v.11 no.11
• /
• pp.1480-1490
• /
• 2008

Design of a linear predictor and matching of an entropy coder is the art of lossless audio coding. In this paper, we use the covariance method and the Choleskey decomposition for calculating linear prediction coefficients instead of the autocorreation method and the Levinson-Durbin recursion. These results are compared to the polynomial predictor. Both of them, the predictor which has small prediction error is selected. For the entropy coding, we use the Golomb-Rice coder using the block-based parameter estimation method and the sequential adaptation method with LOCO-land RLGR. The proposed predictor and the block-based parameter estimation have $2.2879%{\sim}0.3413%$ improved compression ratios compared to FLAC lossless audio coder which use the autocorrelation method and the Levinson-Durbin recursion. The proposed predictor and the LOCO-I adaptation method could improved by $2.2879%{\sim}0.3413%$. But the proposed predictor and the RLGR adaptation method got better results with specific signals.

• Journal of Information Processing Systems
• /
• v.11 no.4
• /
• pp.601-615
• /
• 2015

Region of interest (ROI) is the most informative part of a medical image and mostly has been used as a major part of watermark. Various shapes ROIs selection have been reported in region-based watermarking techniques. In region-based watermarking schemes an image region of non-interest (RONI) is the second important part of the image and is used mostly for watermark encapsulation. In online healthcare systems the ROI wrong selection by missing some important portions of the image to be part of ROI can create problem at the destination. This paper discusses the complete medical image availability in original at destination using the whole image as a watermark for authentication, tamper localization and lossless recovery (WITALLOR). The WITALLOR watermarking scheme ensures the complete image security without of ROI selection at the source point as compared to the other region-based watermarking techniques. The complete image is compressed using the Lempel-Ziv-Welch (LZW) lossless compression technique to get the watermark in reduced number of bits. Bits reduction occurs to a number that can be completely encapsulated into image. The watermark is randomly encapsulated at the least significant bits (LSBs) of the image without caring of the ROI and RONI to keep the image perceptual degradation negligible. After communication, the watermark is retrieved, decompressed and used for authentication of the whole image, tamper detection, localization and lossless recovery. WITALLOR scheme is capable of any number of tampers detection and recovery at any part of the image. The complete authentic image gives the opportunity to conduct an image based analysis of medical problem without restriction to a fixed ROI.

• IEIE Transactions on Smart Processing and Computing
• /
• v.6 no.4
• /
• pp.292-298
• /
• 2017

The complexity of image compression algorithms has increased in order to improve image compression efficiency. One way to resolve high computational complexity is parallel processing. However, entropy coding, which is lossless compression, does not fit into the parallel processing form because of the correlation between consecutive symbols. This paper proposes a new application-specific instruction set processor (ASIP) platform by adding new context-adaptive binary arithmetic coding (CABAC) instructions to the existing platform to quickly process a variety of entropy coding. The newly added instructions work without conflicts with all other existing instructions of the platform, providing the flexibility to handle many coding standards with fast processing speeds. CABAC software is implemented for High Efficiency Video Coding (HEVC) and the performance of the proposed ASIP platform was verified with a field programmable gate array simulation.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.9
• /
• pp.124-132
• /
• 1994

An image data compression method for a digital VCR must satisfy special requirements such as high speed playback. various edting capabilities and error concealment to provide immunity to tape dropouts. Taking these requirements requirements into consideration, this paper proposes a new interframe subband coding algorithm for a digital VCR. In the proposed method, continuous input images are fist partitioned into four frequency bands. The lowest frequency subband is coded with 3-D block adaptive quantization that removes the level redundancy within each level. The other higher frequency subbands are coded by an intraframe coding method using the property of the human visual system. To keep reasonable image quality in high speed palyback, a segment forming method in the frequency domaing is also proposed Computer simulation results demonstrate that the proposed algorithm has the potential of achieving virtually lossless compression in normal play and produces an image with less mosaic errors in high speed play.

• Proceedings of the KOSOMBE Conference
• /
• v.1991 no.11
• /
• pp.54-56
• /
• 1991

Many techniques have been used for medial image compression. Its first requirement is "Errorless" or, "Completely Reversible". Under this condition, we have increased the performance of compression using Space Filling Curve. This method converts source image in direction of Hilbert's curve path in order to ate average length longer thar in traditoinal horizental normal path. After that, we have applied RLC and reduced statistical redundancy by Huffman Coding. By this method, we have obtained more efficient results of RLC.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1998.06b
• /
• pp.165-170
• /
• 1998

This paper presents a new prediction method RBP region-based prediction model where the context used for prediction contains regions instead of individual pixels. There is a meaningful property that RBP can partition a cartoon image into two distinctive types of regions, one containing full-color backgrounds and the other containing boundaries, edges and home-chromatic areas. With the development of computer techniques, synthetic images created with CG (computer graphics) becomes attactive. Like the demand on data compression, it is imperative to efficiently compress synthetic images such as cartoon animation generated with CG for storage of finite capacity and transmission of narrow bandwidth. This paper a lossy compression method to full-color regions and a lossless compression method to homo-chromatic and boundaries regions. Two criteria for partitioning are described, constant criterion and variable criterion. The latter criterion, in form of a linear function, gives the different threshold for classification in terms of contents of the image of interest. We carry out experiments by applying our method to a sequence of cartoon animation. We carry out experiments by applying our method to a sequence of cartoon animation. Compared with the available image compression standard MPEG-1, our method gives the superior results in both compression ratio and complexity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2000.11b
• /
• pp.87-92
• /
• 2000

본 논문에서는 컨텍스트 기반 계층적 열거 부호화를 이용한 무손실 이진 영상 압축 알고리즘을 제안한다. 이진 영상내에 존재하는 인접한 화소간의 상호상관성을 이용하여 이진 영상을 1차원의 수열로 재구성하고, 이에 대해 계층적 열거 부호화를 실행한다. 제안하는 알고리즘은 덧셈 및 비교 연산만으로 구현이 가능하므로 그 복잡도가 매우 낮을 뿐만 아니라, CCITT 테스트 영상을 대상으로 한 부호화 성능 실험에서 우수한 성능을 나타낸다. 부호화 성능 비교에서 이진 영상 부호화 국제표준인 JBIG, G3, G4 및 GIF에 비해 우수한 압축 성능을 보인다.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2001.06a
• /
• pp.261-264
• /
• 2001

논문에서는 S+P 웨이브릿 변환과 정수 웨이브릿 필터들을 비교 분석하고, 9/7텝 정수 웨이브릿 필터를 이용하여 웨이브릿 변환을 하고, 점진적 전송에 적합 하고, 다중 분해능 구조의 종속성과 방향성에 대한 고려와 예측오차의 피드백을 이용한 컨텍스트 모델링 예측과 적응산술부호화에 의한 엔트로피 코딩 방법을 제안하였다. 다양한 영상들에 대한 실험을 통해 본 논문에서 제안한 무손실 영상 압축알고리즘을 S+P 웨이브릿을 이용한 결과와 비교하였다.