Optimal entropy-constrained non-uniform scalar quantizer design for low bit-rate pixel domain DVC

In this paper, an optimal entropy-constrained non-uniform scalar quantizer is proposed for the pixel domain DVC. The uniform quantizer is efficient for the hybrid video coding since the residual signals conforming to a single-variance Laplacian distribution. However, the uniform quantizer is not opt...

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Veröffentlicht in:Multimedia tools and applications Jg. 70; H. 3; S. 1799 - 1824
Hauptverfasser: Wu, Bo, Zhang, Nan, Ma, Siwei, Zhao, Debin, Gao, Wen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.06.2014
Springer
Springer Nature B.V
Schlagworte:
Algorithms
Analysis
Applied sciences
Artificial intelligence
Biomedical engineering
Codes
Coding, codes
Computer Communication Networks
Computer Science
Computer science; control theory; systems
Counters
Data Structures and Information Theory
Design
Dynamic programming
Efficiency
Entropy
Exact sciences and technology
Information, signal and communications theory
Multimedia communications
Multimedia Information Systems
Optimization
Partitions
Pattern recognition. Digital image processing. Computational geometry
Pixels
Quantization
Scalars
Signal and communications theory
Special Purpose and Application-Based Systems
Studies
Telecommunications and information theory
Tradeoffs
DVC
Optimal quantizer
Non-uniform scalar quantizer
Video coding
Histogram
Lagrangian
Rate distortion theory
Mixture theory
Updating
Iterative method
Conditional probability
Joint distribution
Adaptive method
Laplacian
Variance
Image quality
Image coding
Signal quantization
Probability density function
Low bit rate
Multiple channel
Monotonicity
ISSN:1380-7501, 1573-7721
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Zusammenfassung:In this paper, an optimal entropy-constrained non-uniform scalar quantizer is proposed for the pixel domain DVC. The uniform quantizer is efficient for the hybrid video coding since the residual signals conforming to a single-variance Laplacian distribution. However, the uniform quantizer is not optimal for pixel domain distributed video coding (DVC). This is because the uniform quantizer is not adaptive to the joint distribution of the source and the SI, especially for low level quantization. The signal distribution of pixel domain DVC conforms to the mixture model with multi-variance. The optimal non-uniform quantizer is designed according to the joint distribution, the error between the source and the SI can be decreased. As a result, the bit rate can be saved and the video quality won’t sacrifice too much. Accordingly, a better R-D trade-off can be achieved. First, the quantization level is fixed and the optimal RD trade-off is achieved by using a Lagrangian function J ( Q ). The rate and distortion components is designed based on P ( Y | Q ). The conditional probability density function of SI Y depend on quantization partitions Q , P ( Y | Q ), is approximated by a Guassian mixture model at encocder. Since the SI can not be accessed at encoder, an estimation of P ( Y | Q ) based on the distribution of the source is proposed. Next, J ( Q ) is optimized by an iterative Lloyd-Max algorithm with a novel quantization partition updating algorithm. To guarantee the convergence of J ( Q ), the monotonicity of the interval in which the endpoints of the quantizer lie must be satisfied. Then, a quantizer partition updating algorithm which considers the extreme points of the histogram of the source is proposed. Consequently, the entropy-constrained optimal non-uniform quantization partitions are derived and a better RD trade-off is achieved by applying them. Experiment results show that the proposed scheme can improve the performance by 0.5 dB averagely compared to the uniform scalar quantization.
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ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-012-1210-1