MPEG motion picture coding with long-term constraint on distortion variation

Wang, Kai; Woods, John W.

doi:10.1117/12.584960

Cited by 5 publications

(5 citation statements)

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“…Flowchart of the proposed method: parameter estimation (block S), bit allocation (block BA), and video encoding (block E). 22,24,26,28,30,32,34,36,38,40. The corresponding R-D points recorded at the encoder output are then used to estimate the parameters (α n , β n ) for each frame, as explained in Section II-D.…”

Section: A Implementationmentioning

confidence: 99%

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Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

Fiengo

Chierchia

Cagnazzo³

et al. 2017

IEEE Trans. on Image Process.

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Abstract-Optimal rate allocation is among the most challenging tasks to perform in the context of predictive video coding, because of the dependencies between frames induced by motion compensation. In this paper, using a recursive rate-distortion model that explicitly takes into account these dependencies, we approach the frame-level rate allocation as a convex optimization problem. This technique is integrated into the recent HEVC encoder, and tested on several standard sequences. Experiments indicate that the proposed rate allocation ensures a better performance (in the rate-distortion sense) than the standard HEVC rate control, and with a little loss w.r.t. an optimal exhaustive research which is largely compensated by a much shorter execution time.

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Section: A Implementationmentioning

confidence: 99%

“…The MINMAX criterion can be optimized through dynamic programming [30], multi-pass approaches [31], [32], or adhoc iterative methods with lower encoding complexity [33]. However, it is not clear whether the MINMAX is always a better criterion than the more classical one.…”

Section: A Related Workmentioning

confidence: 99%

Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

Fiengo

Chierchia

Cagnazzo³

et al. 2017

IEEE Trans. on Image Process.

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“…Step 2.3: Encode the n th frame at QP n and s T n to obtain the encoded bit rate R n (QP n , s T n ). Step 2.3: ComputeR n (QP n , s d ) using (10). Calculate θ(s d ) and c with (11) and (12).…”

Section: B Proposed Aro Rate Control Algorithmmentioning

confidence: 99%

“…Rate-distortion models and quality metrics have been developed in order to operate the encoder at the best quality given the bit rate constraint [6], [7]. When high computational complexity is affordable, multiple encoding passes facilitate the encoder in learning the video contents and refining the encoding procedures, usually on bit allocation and quantization parameter calculation [8]- [10]. In general, a good rate control algorithm allocates the available bits to the video data such that the quality is optimal; and provides a mechanism to encode the video data at approximately the target number of bits.…”

Section: Introductionmentioning

confidence: 99%

A Fine Rate Control Algorithm With Adaptive Rounding Offsets (ARO)

Xu¹,

Lu²,

Liu

et al. 2009

IEEE Trans. Circuits Syst. Video Technol.

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Rate control plays an important role in regulating the bit rate to meet the bandwidth and storage requirement. Most existing video encoders regulate the bit rate by adjusting the quantization step size. We propose to incorporate a new dimension: the quantization rounding offset into rate control. In this paper, we present a rate control algorithm with adaptive rounding offsets (ARO) that jointly adjusts the quantization step size and the rounding offset for high bit rate accuracy. Different from the quantization step size that has a limited number of choices, the rounding offset is a continuously adjustable variable that allows the rate control algorithm to reach any precision in principle. Our extensive experimental results show that the proposed ARO algorithm significantly improves the rate control accuracy at almost no extra computational complexity. Compared with the ρ-domain rate control, the ARO algorithm reduces the rate control errors from about 2% to 0.5% for INTRA frames, and 5% to 1.5% for INTER frames. Our experiments also demonstrate that ARO provides the extra benefit of smoother visual quality.

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“…However, almost all the existing MINMAXbased methods [18]- [21] focus on minimizing the quality variation among frames, and none aims for constant quality inside a frame. This is understandable because the distortion/quality metrics that been used in these works are usually the mean square error (MSE) or the peak signal to noise ratio (PSNR).…”

Section: Introductionmentioning

confidence: 99%

QP Selection Optimization for Intra-Frame Encoding Based on Constant Perceptual Quality

Wang

Mou

Zhang

2016

IEICE Trans. Inf. & Syst.

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SUMMARYIn lossy image/video encoding, there is a compromise between the number of bits and the extent of distortion. Optimizing the allocation of bits to different sources, such as frames or blocks, can improve the encoding performance. In intra-frame encoding, due to the dependency among macro blocks (MBs) introduced by intra prediction, the optimization of bit allocation to the MBs usually has high complexity. So far, no practical optimal bit allocation methods for intra-frame encoding exist, and the commonly used method for intra-frame encoding is the fixed-QP method. We suggest that the QP selection inside an image/a frame can be optimized by aiming at the constant perceptual quality (CPQ). We proposed an iteration-based bit allocation scheme for H.264/AVC intra-frame encoding, in which all the local areas (which is defined by a group of MBs (GOMBs) in this paper) in the frame are encoded to have approximately the same perceptual quality. The SSIM index is used to measure the perceptual quality of the GOMBs. The experimental results show that the encoding performance on intra-frames can be improved greatly by the proposed method compared with the fixed-QP method. Furthermore, we show that the optimization on the intra-frame can bring benefits to the whole sequence encoding, since a better reference frame can improve the encoding of the subsequent frames. The proposed method has acceptable encoding complexity for offline applications.

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MPEG motion picture coding with long-term constraint on distortion variation

Cited by 5 publications

References 0 publications

Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

Rate Allocation in Predictive Video Coding Using a Convex Optimization Framework

A Fine Rate Control Algorithm With Adaptive Rounding Offsets (ARO)

QP Selection Optimization for Intra-Frame Encoding Based on Constant Perceptual Quality

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