• Title/Summary/Keyword: Fractal coding

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영상압축 : Digital Image Compression

  • Kim, Gyeong-Seop
    • Korean Journal of Digital Imaging in Medicine
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    • v.4 no.1
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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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Design and Implementation of Real-time Moving Picture Encoder Based on the Fractal Algorithm (프랙탈 알고리즘 기반의 실시간 영상 부호화기의 설계 및 구현)

  • Kim, Jae-Chul;Choi, In-Kyu
    • The KIPS Transactions:PartB
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    • v.9B no.6
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    • pp.715-726
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    • 2002
  • In this paper, we construct real-time moving picture encoder based on fractal theory by using general purpose digital signal processors. The constructed encoder is implemented using two fixed-point general DSPs (ADSP2181) and performs image encoding by three stage pipeline structure. In the first pipeline stage, the image grabber acquires image data from NTSC standard image signals and stores digital image into frame memory. In the second stage, the main controller encode image dada using fractal algorithm. The last stage, output controller perform Huffman coding and result the coded data via RS422 port. The performance tests of the constructed encoder shows over 10 frames/sec encoding speed for QCIF data when all the frames are encoded. When we encode the images using the interframe and redundency based on the proposed algorithms, encoding speed increased over 30 frames/sec in average.

A Novel Fractal Coding Method for Image Communication (영상통신을 위한 새로운 프랙탈 부호화 기법)

  • 김정일;김병천
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.3
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    • pp.99-106
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    • 1998
  • This Paper proposes a novel fractal image method for image communication to shorten time to take on fractal encoding by using limited search area method and scaling method First, the original image is contracted respectively by half and by quarter with the scaling 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 quality than Jacquin's method.

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A Study on fast LIFS Image Coding Using Adaptive Orthogonal Transformation (적응 직교변환을 이용한 LIFS 부호화의 고속화에 관한 연구)

  • 유현배;박경남;박지환
    • Journal of Korea Multimedia Society
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    • v.7 no.5
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    • pp.658-667
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    • 2004
  • For digital image compression, various fractal image coding schemes using the self-similarity of image have been studied extensively. This paper discusses the problem that occurs during the calculating process of adaptive orthogonal transformation and provides improvements of LIFS coding scheme using the transformation. This proposed scheme has a better performance than JPEG for a wide range of compression ratio. This research also proposes an image composition method consisting of all domains of the transformation. The results show that the arithmetic operation processes of the encoder and the decoder become much smaller even without the distortion of the coding performance.

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ECG Data Compression Using Adaptive Fractal Interpolation (적응 프랙탈 보간을 이용한 심전도 데이터 압축)

  • 전영일;윤영로
    • Journal of Biomedical Engineering Research
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    • v.17 no.1
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    • pp.121-128
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    • 1996
  • This paper presents the ECG data compression method referred the adaptive fractal interpolation algorithm. In the previous piecewise fractal interpolation(PFI) algorithm, the size of range is fixed So, the reconstruction error of the PFI algorithm is nonuniformly distributed in the part of the original ECG signal. In order to improve this problem, the adaptive fractal interpolation(AEI) algorithm uses the variable range. If the predetermined tolerance was not satisfied, the range would be subdivided into two equal size blocks. large ranges are used for encoding the smooth waveform to yield high compression efficiency, and the smaller ranges are U for encoding rapidly varying parts of the signal to preserve the signal quality. The suggested algorithm was evaluated using MIT/BIH arrhythmia database. The AEI algorithm was found to yield a relatively low reconstruction error for a given compression ratio than the PFI algorithm. In applications where a PRD of about 7.13% was acceptable, the ASI algorithm yielded compression ratio as high as 10.51, without any entropy coding of the parameters of the fractal code.

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Block Loss Recovery Using Fractal Extrapolation for Fractal Coded Images (프랙탈 외삽을 이용한 프랙탈 부호화 영상에서의 블록 손실 복구)

  • 노윤호;소현주;김상현;김남철
    • Journal of Broadcast Engineering
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    • v.4 no.1
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    • pp.76-85
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    • 1999
  • The degradation of image quality by block loss is more serious in fractal coded images with the error propagation due to mapping from the lost blocks than in DCT coded images. Therefore. a new algorithm is presented for recovering the blocks lost in the transmission through the lossy network as A TM network of the images coded by Jacquins fractal coding. Jacquins fractal code is divided into two layers of header code and main code according to its importance. The key technique of the proposed BLRA (block loss recovery algorithm) is a fractal extrapolation that estimates the lost pixels by using the contractive mapping parameters of the neighboring range blocks whose characteristics are similar to a lost block. The proposed BLRA is applied to the lost blocks in the iteration of decoding. Some experimental results show the proposed BLRA yields excellent performance in PSNR as well as subjective quality.

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A Study on Decoding Characteristic Analysis of Non-iterative Fractal Image Compression (무반복 프랙탈 영상 압축의 복호 특성 분석에 관한 연구)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.5 no.3
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    • pp.199-204
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    • 2004
  • A problem of many fractal image compression algorithms providing good quality at low bit rate is that the decoding time rests on an iterative procedure whose complexity is imag-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding time could be remarkably reduced. For verifying the validity and universality of proposed method, We evaluated and analyzed the performance of decoding time and image quality for a number of still images and a moving picture with different distributed characteristics.

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Fractal Image Coding in Wavelet Transform Domain Using Absolute Values of Significant Coefficient Trees (유효계수 트리의 절대치를 이용한 웨이브릿 변화 영역에서의 프랙탈 영상 압축)

  • Bae, Sung-Ho;Kim, Hyun-Soon
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.4
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    • pp.1048-1056
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    • 1998
  • In this paper, a fractal image coding based on discrete wavelet transform is proposed to improve PSNR at low bit rates and reduce computational complexity of encoding process. The proposed method takes the absolute value of discrete wavelet transform coefficients, and then constructs significant coefficients trees, which indicate the positions and signs of the significant coefficients. This method improves PSNR and reduces computational complexity of mapping contracted domain pool onto range block, by matching only the significant coefficients of range block to coefficients of contracted domain block. Also, this paper proposes a classification scheme which minimizes the number of contracted domain blocks compared with range block. This scheme significantly reduces the number of range and contracted domain block comparison.

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(Very Low Bitrate Image Compression Coding Based on Fractal) (프랙탈 기반 저전송율 영상 압축 부호화)

  • 곽성근
    • Journal of the Korea Computer Industry Society
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    • v.3 no.8
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    • pp.1085-1092
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    • 2002
  • Studies on image information processing have been performed since long time ago because in daily life most of information are acquired by the since of sight. Since there should be a lot of data to describe image as a digital form, data compression is required in order to store or transmit digital image. Lately among most of image compression methods adopted on image compression standards, transform coding methods have been primarily used which transforms the correlations between pixels of image on frequency domain before image compression. It is blown that the standard methods using especially DCT features blocking effect which is the major cause of degrading the quality of image at high compression rate. Fractal encoding using quadtree partition is applied after reducing original image, and we are to find a optimal encoding for the number of scaling bit and offset bit.

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Sub-optimal fractal Coding Scheme Using Iterative Transformation (반복 변환을 이용한 준최적 프랙탈 부호화 기법)

  • 강현수;홍성훈
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.3A
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    • pp.231-239
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    • 2002
  • This paper presents a new fractal coding scheme to find sub-optimal transformation by performing an iterative encoding process. An optimal transformation can be defined as the transformation generating the attractor which is closest to an original image. Unfortunately, it has been well-known that it is actually impossible to find the optimal transformation due to heavy computation. In this paper, however, by means of some new theorems related with the fractal transformation due the attractor, it is shown that for a special case the optimal transformation can be obtained as well as for a general case the sub-optimal transformation. The proposed method based on the theorems obtains the sub-optimal transformation performing an iterative process as if done in decoding. Thus, it requires more computation than the conventional method but improves the image quality. We verify the superiority of the proposed method through the experimental results fur real images, which shows that the proposed method approaches to the optimal method in the performance and is superior to the conventional method.