• Title/Summary/Keyword: Adaptive allocation coefficient

Search Result 4, Processing Time 0.019 seconds

An Adaptive Estimation Model for Propagation Errors Incurred by CD in FD-CD Transcoding (FD-CD 트랜스코딩기법에서 CD에 의한 전파 왜곡의 적응적 예측 모델)

  • Kim Jin-soo;Kim Jae-Gon
    • Journal of Korea Multimedia Society
    • /
    • v.7 no.11
    • /
    • pp.1571-1579
    • /
    • 2004
  • Recently, FD(Frame Dropping)-CD(Coefficient Dropping) transcoding is considered mainly due to the low computational complexity and simple implementation. But, CD errors in the FD-CD transtoding scheme tend to be propagated and they have a significant effect on the qualities of decoded images. In this paper, we derive the error characteristics incurred by the CD operations and propose an effective estimation model that adaptively describes well the characteristics of propagation/accumulation errors in compressed domain. Furthermore, we apply the proposed model to distortion control achieving nearly constant distortion allocation among frames. Simulation results show that the proposed model is quite accurate in estimating the overall distortions and is effectively applied to distortion control over a range of sequences with varying scene types.

  • PDF

Adaptive coding algorithm using quantizer vector codebook in HDTV (양자화기 벡터 코드북을 이용한 HDTV 영상 적응 부호화)

  • 김익환;최진수;박광춘;박길흠;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.31B no.10
    • /
    • pp.130-139
    • /
    • 1994
  • Video compression algorithms are based on removing spatial and/or temproal redundancy inherent in image sequences by predictive(DPCM) encoding, transform encoding, or a combination of predictive and transform encoding. In this paper, each 8$\times$8 DCT coefficient of DFD(displaced frame difference) is adaptively quantized by one of the four quantizers depending on total distortion level, which is determined by characteristics of HVS(human visual system) and buffer status. Therefore, the number of possible quantizer selection vectors(patterns) is 4$^{64}$. If this vectors are coded, toomany bits are required. Thus, the quantizer selection vectors are limited to 2048 for Y and 512 for each U, V by the proposed method using SWAD(sum of weighted absolute difference) for discriminating vectors. The computer simulation results, using the codebook vectors which are made by the proposed method, show that the subjective and objective image quality (PSNR) are goor with the limited bit allocation. (17Mbps)

  • PDF

Performance Analysis of DVC Scheme with Adaptive Gray Code for Frame Difference Signal (화면 간 차이신호에 대한 적응적 그레이코드를 이용한 분산 비디오 부호화 기법의 성능 분석)

  • Kim, Jin-Soo;Kim, Jae-Gon;Choi, Hae-Chul
    • Journal of Broadcast Engineering
    • /
    • v.17 no.5
    • /
    • pp.876-890
    • /
    • 2012
  • In this paper, we investigated the performances of the distributed video codec with adaptive Gray code to apply for frame-difference signal. That is, the best cases and the worst cases were analyzed and compared by considering the statistical characteristics of the frame difference signal in view of the Gray code allocation. Through computer simulations, if 9-bit data for frame difference signal is generated for luminance signal with 8-bit definition and so n-bit is allocated to the quantized coefficient, we were able to find the best method to reduce the virtual channel noise by adding $256+2^{9-n-1}$ to the frame difference signal. Through computer simulation with test video sequences, it was shown that the performance difference between the best cases and the worst cases is larger than about 1.5dB at same rate. It is expected that the results in this paper are applicable for the transform-domain scheme as well as the pixel-domain scheme.

Progressive Image Transmission using LOT/CVQ with HVS Weighting (HVS가중치를 갖는 LOT/CVQ를 이용한 점진적 영상 전송)

  • 황찬식
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.18 no.5
    • /
    • pp.685-694
    • /
    • 1993
  • A progressive image transmission (PIT) scheme based on the classified transform vector quantization (CVQ) technique using the lapped orthogonal transform (LOT) and human visual system (HVS) weighting is proposed in this paper. Conventional block transform coding of images using DCT produces in general undesirable block-artifacts at low bit rates. In this paper, image blocks are transformed using the LOT and classified into four classes based on their structural properties and further divided adaptively into subvectors depending on the LOT coefficient statistics with HVS weighting to improve the reconstructed image quality by adaptive bit allocation. The subvectors are vector quantized and transmitted progressively. Coding tests using computer simulations show that the LOT/CVQ based PIT of images is a effective coding scheme. The results are also compared with those obtained using PIT/DCTVQ. The LOT/CVQ based PIT reduces the block-artifacts significantly.

  • PDF