Rate-distortion optimization using structural information in H.264 strictly Intra-frame encoder

Aswathappa, Babu Hemanth Kumar; Rao, K. R.

doi:10.1109/ssst.2010.5442789

Cited by 12 publications

(7 citation statements)

References 12 publications

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“…Indeed, a significant amount of effort has been made to improve video compression efficiency whilst maintaining SSIM-based video quality. For example, SSIM has been incorporated into H.264/AVC coding mode selection [10], Motion Estimation (ME) [11], and RDO algorithms [12], [13], [14], [15], [16], [17], [18], [19], [20], [21]. Most recently, SSIM optimization has also been embedded into HEVC, leading to notable coding gain [22].…”

Section: Introductionmentioning

confidence: 99%

“…It is also worth noting that in the use of SSIM in video coding, a number of variations have been employed in the computation of SSIM to better fit the computational structures of video coding algorithms. For example, as opposed to the 2D Gaussian sliding window employed in the original SSIM computation [6], different sizes of square windows have been used to calculate block SSIM, including 16×16 sliding windows in [12], [10], [11], [15], 8×8 sliding windows in [13], [14] and 8×8 non-overlapping windows in [16], [19], [20], [21]. In [12], [10], [11], [15], [16], [19], SSIM of a block is obtained by averaging the SSIM values of its 4×4 non-overlapping child blocks, in [13], [14], block SSIM is calculated in the full current block directly, while in [20], [21], 4×4 sliding windows are used for SSIM calculation in an extended block.…”

Section: Introductionmentioning

confidence: 99%

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On the use of SSIM in HEVC

Zhao

Zeng

Rehman

et al. 2013

2013 Asilomar Conference on Signals, Systems and Computers

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The Structural SIMilarity (SSIM) index has been attracting an increasing amount of attention recently in the video coding community as a perceptual criterion for testing and optimizing video codecs. Meanwhile, the arrival of the new MPEG-H/H.265 High Efficiency Video Coding (HEVC) standard creates new opportunities and challenges in perceptual video coding. In this paper, we first elaborate what are the attributes that make SSIM a good candidate for perception-based development of HEVC and future video coding standards for both testing and optimization purposes. We then address the computational issues in practical applications of SSIM in HEVC, in particular the trade-off between efficient computation and accurate estimation of SSIM when working with video codecs that have sophisticated block partitioning structures and aim for encoding videos with a wide range of spatial resolutions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the use of SSIM in HEVC

Zhao

Zeng

Rehman

et al. 2013

2013 Asilomar Conference on Signals, Systems and Computers

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“…Recently, SSIM has been incorporated into Motion Estimation (ME), mode selection and rate control algorithms, to enhance compression efficiency whilst maintaining the perceptual quality [27]- [38]. Mai et al [27], [28] and Aswathappa and Rao [29] independently proposed SSIMbased intra prediction mode decision methods, with a fixed LM for each Quantization Parameter (Qp). In [30], SSIM was employed to improve ME process in H.264 to achieve more BR reduction with the same perceptual video quality.…”

Section: Introductionmentioning

confidence: 99%

SSIM-Based Coarse-Grain Scalable Video Coding

Zhao

Wang

Zhou

et al. 2015

IEEE Trans. on Broadcast.

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We propose an improved coarse-grain scalable video coding (SVC) approach based on the structural similarity (SSIM) index as the visual quality criterion, aiming at maximizing the overall coding performance constrained by user-defined quality weightings for all scalable layers. First, we develop an interlayer rate-SSIM dependency model, by investigating bit rate and SSIM relationships between different layers. Second, a reduced-reference SSIM-Q model and a Laplacian R-Q model are introduced for SVC, by incorporating the characteristics of hierarchical prediction structure in each layer. Third, based on the user-defined weightings and the proposed models, we design a rate-distortion optimization approach to adaptively adjust Lagrange multipliers for all layers to maximize the overall rate-SSIM performance of the scalable encoder. Experiments with multiple layers, different layer weightings, and various videos demonstrate that the proposed framework can achieve better rate-SSIM performance than single layer optimization method, and provide better coding efficiency as compared to the conventional SVC scheme. Subjective tests further demonstrate the benefits of the proposed scheme.

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“…Since SSIM is proven to be more effective in quantifying the suprathreshold compression artifacts, such as artifacts that distort the structure of an image [27], it was incorporated into motion estimation, mode selection, and rate control in hybrid video coding [28]- [38]. For intra frame coding, new SSIMbased RDO schemes were proposed in [28]- [30].…”

mentioning

confidence: 99%

“…For intra frame coding, new SSIMbased RDO schemes were proposed in [28]- [30]. In [31]- [33], the authors developed SSIM-based RDO schemes for inter frame prediction and mode selection.…”

mentioning

confidence: 99%

SSIM-Motivated Rate-Distortion Optimization for Video Coding

Wang

Rehman

Wang

et al. 2012

IEEE Trans. Circuits Syst. Video Technol.

193

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Abstract-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.Index Terms-H.264/AVC coding, Lagrange multiplier, rate-distortion optimization, reduced-reference image quality assessment, structural similarity (SSIM) index.

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Rate-distortion optimization using structural information in H.264 strictly Intra-frame encoder

Cited by 12 publications

References 12 publications

On the use of SSIM in HEVC

On the use of SSIM in HEVC

SSIM-Based Coarse-Grain Scalable Video Coding

SSIM-Motivated Rate-Distortion Optimization for Video Coding

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