• 제목/요약/키워드: Lossy Compression

검색결과 132건 처리시간 0.024초

LOSSY JPEG CHARACTERISTIC ANALYSIS OF METEOROLOGICAL SATELLITE IMAGE

  • Kim, Tae-Hoon;Jeon, Bong-Ki;Ahn, Sang-Il;Kim, Tae-Young
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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    • pp.282-285
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    • 2006
  • This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

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무손실.손실 영상 압축을 위한 웨이브릿 기반 알고리즘에 관한 연구 (A Study on the Wavelet Based Algorithm for Lossless and Lossy Image Compression)

  • 안종구;추형석
    • 대한전기학회논문지:시스템및제어부문D
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    • 제55권3호
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    • pp.124-130
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    • 2006
  • A wavelet-based image compression system allowing both lossless and lossy image compression is proposed in this paper. The proposed algorithm consists of the two stages. The first stage uses the wavelet packet transform and the quad-tree coding scheme for the lossy compression. In the second stage, the residue image taken between the original image and the lossy reconstruction image is coded for the lossless image compression by using the integer wavelet transform and the context based predictive technique with feedback error. The proposed wavelet-based algorithm, allowing an optional lossless reconstruction of a given image, transmits progressively image materials and chooses an appropriate wavelet filter in each stage. The lossy compression result of the proposed algorithm improves up to the maximum 1 dB PSNR performance of the high frequency image, compared to that of JPEG-2000 algorithm and that of S+P algorithm. In addition, the lossless compression result of the proposed algorithm improves up to the maximum 0.39 compression rates of the high frequency image, compared to that of the existing algorithm.

사분트리 알고리즘과 기하학적 웨이블렛을 이용한 손실 영상 압축 (Lossy Image Compression Based on Quad Tree Algorithm and Geometrical Wavelets)

  • 추형석;안종구
    • 전기학회논문지
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    • 제58권11호
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    • pp.2292-2298
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    • 2009
  • In this paper, the lossy image compression algorithm using the quad tree and the bandlets is proposed. The proposed algorithm transforms input images by the discrete wavelet transform (DWT) and represents the geometrical structures of high frequency bands using the bandlets with a 8 block- size. In addition, the proposed algorithm searches the position information of the significant coefficients by using the quad tree algorithm and computes the magnitude and the sign information of the significant coefficients by using the Embedded Image Coding using Zerotrees of Wavelet Coefficients (EZW) algorithm. The compression result by using the quad tree algorithm improves the PSNR performance of high frequency images up to 1 dB, compared to that of JPEG-2000 algorithm and that of S+P algorithm. The PSNR performance by using DWT and bandlets improves up to 7.5dB, compared to that by using only DWT.

JPEG 재 압축이 컬러 이미지 품질에 미치는 영향에 관한 연구 (A Study on the effect of JPEG recompression with the color image quality)

  • 이성형;구철회
    • 한국인쇄학회:학술대회논문집
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    • 한국인쇄학회 2000년도 춘계 학술발표회 논문집
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    • pp.17-24
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    • 2000
  • The Joint Photographic Experts Group (JPEG) is a standara still-image compression technique, established by the International for Standardization (ISO) and International Telecommunication Standardization Sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are nto the same as values before compression. Image of JPEG compression is often made to JPEG recompression at saving to apply JPEG compression of color image. In general, JPEG is a lossy compression and compression image is predicted to be varied image quality according to recompressed Q-factor. Various distortions of JPEG compression and JPEG recompression has been reported in previous paper. In this paper, we compress four difference color samples (photo image, gradient image, vector drawing image, text image) according to various Q-factor, and then compressed images are recompressed according to various Q-factor once again. As the results, we inspect variation of quality and file size of recompressed color image, and ensure the optimum recompression factor.

JPEG 재압축이 컬러 이미지 품질에 미치는 영향에 관한 연구 (A study on the effect of JPEG recompression with the color image quality)

  • 이성형;조가람;구철희
    • 한국인쇄학회지
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    • 제18권2호
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    • pp.55-68
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    • 2000
  • Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

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손실 압축을 위한 EZW 알고리즘의 개선에 관한 연구 (A Study on the Improvement of EZW Algorithm for Lossy Image Compression)

  • 추형석;안종구
    • 전기학회논문지
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    • 제56권2호
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    • pp.415-419
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    • 2007
  • Data compression is very important for the storage and transmission of informations. EZW image compression algorithm has been widely used in real application due to its high compression performance. In the EZW algorithm, when a new significant coefficient is generated, its children are all encoded, although its all descendants may be insignificant, and thus its performance is declined. In this paper, we proposed an improved EZW algorithm using IS(Isolated Significant) symbol, which checks all descendants of significant coefficient and avoids encoding the children of each newly generated significant coefficient if it has no significant descendant.

Lossy Source Compression of Non-Uniform Binary Source via Reinforced Belief Propagation over GQ-LDGM Codes

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • ETRI Journal
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    • 제32권6호
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    • pp.972-975
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    • 2010
  • In this letter, we consider the lossy coding of a non-uniform binary source based on GF(q)-quantized low-density generator matrix (LDGM) codes with check degree $d_c$=2. By quantizing the GF(q) LDGM codeword, a non-uniform binary codeword can be obtained, which is suitable for direct quantization of the non-uniform binary source. Encoding is performed by reinforced belief propagation, a variant of belief propagation. Simulation results show that the performance of our method is quite close to the theoretic rate-distortion bounds. For example, when the GF(16)-LDGM code with a rate of 0.4 and block-length of 1,500 is used to compress the non-uniform binary source with probability of 1 being 0.23, the distortion is 0.091, which is very close to the optimal theoretical value of 0.074.

패턴매칭에 의한 이진 한글문서의 유.무손실 압축에 관한 연구 (The Study on Lossy and Lossless Compression of Binary Hangul Textual Images by Pattern Matching)

  • 김영태;고형화
    • 한국통신학회논문지
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    • 제22권4호
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    • pp.726-736
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    • 1997
  • The textual image compression by pattern matching is a coding scheme that exploits the correlations between patterns. When we compress the Hangul (Korean character) text by patern matching, the collerations between patterns may decrease due to randoem contacts between phonemes. Therefore in this paper we separate connected phonemes to exploit effectively the corrlation between patterns by inducting the amtch. In the process of sequation, we decide whether the patterns have vowel component or not, and then vowels connected with consonant ae separated. When we compare the proposed algorithm with the existing algorith, the compression ratio is increased by 1.3%-3.0% than PMS[5] in lossy mode, by 3.4%-9.1% in lossless mode than that of SPM[7] which is submitted to standard committe for second generation binary compression algorithm.

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질환 영역 인식을 통한 MRI 차등 영상 압축 (MRI Image Compression by Using Recognition of Region of Disease)

  • 김현순;배성호;박길흠
    • 한국정보처리학회논문지
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    • 제5권10호
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    • pp.2704-2712
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    • 1998
  • 본 논문에서는 진단에 중요한 정보를 가진 영역에 대해서 무손실 부호화하고 나머지 영역에 대해서는 손실 부호화를 하여 비트를 효율적으로 할당하는 MRI 영상 압축 방법을 제안한다. 제안한 방법에서는 척추 디스크 질환 인식을 위해 촬영된 MRI 영상을 대상으로, 질환의 특성을 이용하여 중요한 객체가 포함된 부분을 인식한다. 인식된 부분은 의사의 디스크 질환 유, 무의 판단에 중요한 부분이므로 무손실 부호화하고 나머지 부분은 손실 부호화하여 전송한다. 또한 손실 부호화하는 영역에 대해서 웨이브릿 변환 영역에서의 프랙탈 압축 방법을 적용하여 블록화 현상이 제거된 선명한 화질을 유지한다.

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영상압축 : Digital Image Compression

  • 김경섭
    • 대한디지털의료영상학회논문지
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    • 제4권1호
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    • pp.166-180
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    • 1998
  • $\cdot$ 영상 압축은 영상의 통계학적 분포, 반복성을 이용하여 빈도가 높은 데이터는 적은 수의 bits를, 빈도가 낮은 데이터에는 보다 많은 수의 bits를 할당하여 전체 영상을 나타내는 bits 수를 줄이는 것임. $\cdot$ 영상 압축은 크게 Lossy Coding, Lossless Coding으로 나뉘며, Lossy coding은 DCT, 양자화기, VLC Codes를 쓰며 압축 율은 높으나 원래의 영상을 정확히 복원하지 못함. $\cdot$ 영상 압축에 대한 국제 규격 협회는 JPEG, MPEG I, MPEG II, MPEG IV, H.261, H.263 등이 있으나 본 seminar에서는 JPEG 규격만 논함. $\cdot$ 의학 영상은 Resolution이 크고 study 단위로 관리되기 때문에 영상 데이터량이 많으나 진단의 목적으로 쓰이기 때문에 주로 lossless 압축을 쓰게 되나 압축율이 낮음.(3:1 이하). 최근에는 Fractal, Wavelet Coding을 통한 압축율을 증가 시키는 Image Compression Algorithms이 활용됨. $\cdot$ MPEG은 동영상의 압축 표준안이며, 동영상은 한frame 당 25개 이상의 정지 화상으로 이루어지기 때문에 JPEG 규격에서 사용되었던 기법이 그대로 활용되며 영상과 영상간, 또는 frame과 frame 간의 여상의 변화, 움직임을 Vector로 coding하는 interframe Coding 기법을 활용하나 설명하기에는 광범위한 topic이므로 본 seminar에서는 생략함.

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