Intraframe coding for picture transmission

Connor, D. J.; Brainard, R. C.; Limb, J.O.

doi:10.1109/proc.1972.8777

Cited by 35 publications

(4 citation statements)

References 49 publications

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“…The encoder we intend to optimize is based on intra-frame encoder techniques (Connor, Brainard, & Limb, 1972), but has been extrapolated to inter-frame coding (Brofferio & Rocca, 1977), basically using a video scene motion detection system (MMS) with the aim of performing simple motion compensation. It is based on JPEG2000 (ISO/IEC, 2000) and its still images compression method.…”

Section: Decision Variablesmentioning

confidence: 99%

MIJ2K Optimization using evolutionary multiobjective optimization algorithms

Bustamante

2011

Expert Systems with Applications

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This paper deals with the multiobjective definition of video compression and its optimization. The opti-mization will be done using NSGA-II, a welltested and highly accurate algorithm with a high conver-gence speed developed for solving multiobjective problems. Video compression is defined as a problem including two competing objectives. We try to find a set of optimal, so-called Pareto-optimal solutions, instead of a single optimal solution. The two competing objectives are quality and compression ratio maximization. The optimization will be achieved using a new patent pending codec, called MIJ2K, also outlined in this paper. Video will be compressed with the MIJ2K codec applied to some classical vid-eos used for performance measurement, selected from the Xiph.org Foundation repository. The result of the optimization will be a set of near-optimal encoder parameters. We also present the convergence of NSGA-II with different encoder parameters and discuss the suitability of MOEAs as opposed to classical search-based techniques in this field.

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Section: Decision Variablesmentioning

confidence: 99%

MIJ2K Optimization using evolutionary multiobjective optimization algorithms

Bustamante

2011

Expert Systems with Applications

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“…a. . That is the i,j i,j coefficients in the feedback predictor are chosen equal to the 2-fl autoregressive coefficients in ( 1). For analysis purposes we assume this to be the case although there may be good.…”

Section: Preliminariesmentioning

confidence: 99%

Combined Source-Channel Coding of Images

Modestino

Daut

1979

IEEE Trans. Commun.

136

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“…Thus, the receiver memory is made to track the transmitter memory. Studies [15] indicate that the pixels of the changing area need not be transmitted independently of one another. Various techniques, such as predictive coding, motion-compensation and others have been used to exploit the correlation between these pixels.…”

Section: Frame Replenishment Using Vector Quantizationmentioning

confidence: 99%

Adptive vector quantization for image sequence coding

Sun

Goldberg²

ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing

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In this paper, new algorithms are presented for image sequence coding based upon the combination of frame replenishment and vector quantization.The results reported include both non-adaptive and adaptive vector quantization. The adaptivity is performed bY replenishing the codebook according to the local statistics of the image sequence. A statistical model is used to initiate the adaptive operation. The experimental results demonstrate that good quality reconstructed image sequences at bit rate as low as 0.6 -0.7 bits/pixel are obtained using adaptive algorithms.

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Intraframe coding for picture transmission

Cited by 35 publications

References 49 publications

MIJ2K Optimization using evolutionary multiobjective optimization algorithms

MIJ2K Optimization using evolutionary multiobjective optimization algorithms

Combined Source-Channel Coding of Images

Adptive vector quantization for image sequence coding

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