SSIM-Motivated Rate-Distortion Optimization for Video Coding

We propose a rate-distortion optimization (RDO) scheme based on the structural similarity (SSIM) index, which was found to be a better indicator of perceived image quality than mean-squared error, but has not been fully exploited in the context of image and video coding. At the frame level, an adapt...

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Veröffentlicht in:IEEE transactions on circuits and systems for video technology Jg. 22; H. 4; S. 516 - 529
Hauptverfasser: Shiqi Wang, Rehman, A., Zhou Wang, Siwei Ma, Wen Gao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.04.2012
Institute of Electrical and Electronics Engineers
Schlagworte:
Adaptation models
Applied sciences
Bit rate
Detection, estimation, filtering, equalization, prediction
Discrete cosine transforms
Distortion measurement
Encoding
Exact sciences and technology
H.264/AVC coding
Image processing
Indexes
Information, signal and communications theory
Lagrange multiplier
Optimization
rate-distortion optimization
reduced-reference image quality assessment
Signal and communications theory
Signal processing
Signal, noise
structural similarity (SSIM) index
Telecommunications and information theory
Video coding
Performance evaluation
Image processing
Similarity
Information quantity
Rate distortion theory
Entropy
Statistical estimation
Algorithm
Optimization
Video signal processing
Mean square error
Visual perception
H.264/AVC coding
rate-distortion optimization
Statistical method
Image quality
Image coding
Lagrange multiplier
structural similarity (SSIM) index
Residual impurity
Quality control
reduced-reference image quality assessment
Image evaluation
ISSN:1051-8215, 1558-2205
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Beschreibung
Zusammenfassung:We propose a rate-distortion optimization (RDO) scheme based on the structural similarity (SSIM) index, which was found to be a better indicator of perceived image quality than mean-squared error, but has not been fully exploited in the context of image and video coding. At the frame level, an adaptive Lagrange multiplier selection method is proposed based on a novel reduced-reference statistical SSIM estimation algorithm and a rate model that combines the side information with the entropy of the transformed residuals. At the macroblock level, the Lagrange multiplier is further adjusted based on an information theoretical approach that takes into account both the motion information content and perceptual uncertainty of visual speed perception. Finally, the mode for H.264/AVC coding is selected by the SSIM index and the adjusted Lagrange multiplier. Extensive experiments show that the proposed scheme can achieve significantly better rate-SSIM performance and provide better visual quality than conventional RDO coding schemes.
ISSN:1051-8215
1558-2205
DOI:10.1109/TCSVT.2011.2168269