A robust fine granularity scalability using trellis-based predictive leak

Huang, Hsiang-Chun; Wang, Chung-Neng; Chiang, Tihao

doi:10.1109/tcsvt.2002.800314

Cited by 81 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although our rate allocation and mode selection schemes were designed for SFGSISFGST, with some modifications, they can also be applicable to other FGS-related coding techniques, such as PFGS [2], MC-FGS [3], RFGS [4], and so on. In these cases, several successive MBs can be grouped as a unit (i.e., a node in the multi-stage topology), instead of the spectral band partition, for DP processing.…”

Section: Discussionmentioning

confidence: 99%

Constant-quality rate allocation for spectral fine granular scalable (SFGS) video coding by using dynamic programming approach

Lie

Tseng

Lin

2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)

View full text Add to dashboard Cite

Spectral FGS (SFGS), modified from MPEG-4 FGS, was proposed as a scalable video coding technique that has evener image quality and is more suitable for rate allocation for video smoothness. This paper proposed a unified rate allocation algorithm bascd on SFGS/SFGST to make good tradeuffs between image quality, video smoothness, and temporal scalability, according to users' preferences at the buffer fullness constraint. Our rate allocation algorithm was established on the dynamic programming (DP) technique. It becomes easy to tune the preference by adjusting weighting parameters in the optimized cost function. Experiments show that our algorithm is capable of achieving the same video smoothness as our previous work [8], having more diversity in mode selection between SFGS and SFGST, and guaranteeing no buffer overflow or underflow.

show abstract

Section: Discussionmentioning

confidence: 99%

Constant-quality rate allocation for spectral fine granular scalable (SFGS) video coding by using dynamic programming approach

Lie

Tseng

Lin

2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)

View full text Add to dashboard Cite

show abstract

“…Inspired by the concept of RFGS [7], we propose the idea of leaky/partial prediction over Base MDSQ. In the following sections, we will introduce the basic idea of leaky and partial prediction for layer coding, and then propose new approaches of these prediction schemes to be applied on Base MDSQ.…”

Section: Base Mdsq With Leaky / Partial Leaky Predictionmentioning

confidence: 99%

Multiple description motion compensation video coding with leaky prediction

Chen

2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)

View full text Add to dashboard Cite

Multiple description (MD) coding has been shown to possess excellent error resilience capability for streaming video over lossy packet networks. Multiple description motion compensation coding (MDMC) also is a MD coding with predictive coding scheme. In such a scheme, there will be "drift" error propagation, caused by the mismatch between the reference frames used in encoding and decoding. To control error propagation will usually lose some predictive efficiency. In this paper, we propose a new algorithm based on MD coding with modified multiple description scalar quantization (MDSQ) and leaky predictions to reduce drift without too much lowering of efficiency. Simulation results indicate that the proposed coder with leaky prediction outperforms the normal MDSQ coder even with same prediction scheme. The proposed coder will be applicable for error prone wireless networks. ]

show abstract

“…The base part of the source is available with high probability at the decoder, so we may use it as the prediction reference for video coding. By this method, there is almost no drift in the video decoding over lossy networks.MDSQ-FGS with partial predictionInspired by the concept of RFGS[7], we propose the idea of partial prediction in MDSQ-FGS coding. Partial prediction is a well-known technique to combat error propagation in the predictive coding, at the expense of increased bit rate.…”

mentioning

confidence: 99%

Multiple description motion compensation video coding for MPEG-4 FGS over lossy packet networks

Chen

2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)

View full text Add to dashboard Cite

A novel error resilience coding technique, named Multiple Description Scalar Quantization for FineGranularify Scalability (MDSQ-FGS), is presented to improve the temporal prediction eflciency for video coding over lossy packet networks and wireless channels. Despite easily adapting to the channel bandwidth Jluctuution, the coding eficiency of scalar coding technique is low since only base-layer is used in its motion prediction. But to achieve higher coding eflciency by using high qualify reference fiames in enhancement-layer will make "drift" error propagate, caused by the mismatch between the referenceJ+ames used in encoding and decoding when reference data are lost. MDSQ-FGS video coding scheme based on MD coding with modifkd multiple description scalur quantization (MDSQ) and partial predictions are proposed to control drifting error without too much reduction in eficienq. Simulation results indicate that the proposed coder ou$e$orms the normal MPEG-4 FGS coder for coding eficiency. MDSQ-FGS coder will also be applicable for error prone wireless networks for a mobile station moving between two acce.ss points.

show abstract

A robust fine granularity scalability using trellis-based predictive leak

Cited by 81 publications

References 5 publications

Constant-quality rate allocation for spectral fine granular scalable (SFGS) video coding by using dynamic programming approach

Constant-quality rate allocation for spectral fine granular scalable (SFGS) video coding by using dynamic programming approach

Multiple description motion compensation video coding with leaky prediction

Multiple description motion compensation video coding for MPEG-4 FGS over lossy packet networks

Contact Info

Product

Resources

About